International Journal of Simulation and Process Modelling (54 papers in press)
Two-sided M-Bayesian limits of credibility of reliability parameters in the case of zero-failure data and a case study
by Wanyi Dai, Siqi Li, Mei Zhang, Yueming Hu, Dongfang Mei
Abstract: In this paper, a novel method of two-sided M-Bayesian credible limit is proposed to deal with the interval estimation problem of reliability parameters with exponential distribution in the case of zero-failure data. The properties of two-sided M-Bayesian limits of credibility are discussed and some new theorems are proven, including the impact of the upper bound c of hyper parameters and the influence of different prior distributions of hyper parameters on two-sided M-Bayesian limits of credibility when the reliability of estimation is determined by the exponential distribution. The paper extends the conclusions drawn in two previous studies regarding the relationships among the many kinds of two-sided M-Bayesian limits of credibility and two-sided classical confidence. Finally, a real data set about engine was discussed with different model parameters. By means of an example, the presented method of this paper is compared with the classical confidence limits. The results verified the properties of two-sided M-Bayesian limits of credibility and indicated that the method is efficient and easy to perform.
Keywords: reliability; estimation; two-sided M-Bayesian limits of credibility; zero-failure data.
A novel method of reactive voltage optimisation for a photovoltaic system
by Weimin Zhang, Yanxia Zhang
Abstract: Based on improved dynamic teaching and learning reactive power optimisation technology based on moth drive algorithm, a new method for real-time adaptive reactive power optimisation with photovoltaic system is proposed. By constructing the mathematical model of reactive power voltage control of photovoltaic power station, learning is optimised continuously in the process of teaching and learning. According to real-time data, the optimal cooperation strategy between RPVC/AVC control system and intelligent power grid command is formed, and real-time, adaptive and dynamic control of the system is realised. The simulation results show that the method is reasonable and effective for testing the 220 kV substation and its feeder system.
Keywords: moth drive light algorithm; dynamic teaching and learning reactive power optimisation; photovoltaic; reactive power and voltage coordinated; automatic voltage control.
XML-based DEVS modelling and simulation tracking
by Youcef Dahmani, Hemza Nedjari Benhadj Ali, Abdelkader Boubekeur
Abstract: Discrete Event system Specification (DEVS) is a formalism for discrete event dynamic systems and has been used to represent several classes of dynamic systems. Furthermore, DEVS formalism has known different variants and software implementations to meet specific needs. Performances of these different tools vary significantly. On the other hand, all of these implementations dont necessarily share models and cant capitalise on model reuse and data exchange. Using a meta-language can help to reduce this issue. XML seems to be an appropriate language for helping modellers who dont need strong programming knowledge. Indeed, XML offers several advantages, it is adopted as a standard for information exchange in different domains. These last years, many researchers have focused their works on XML applied to different domains and subjects due to its ability in playing an increasingly important role in the exchange of a wide variety of data on the web. This work aims at determining an XML-based implementation of DEVS formalism, for devising an efficient modelling and simulation framework. It consists not only in using XML schemas to define the vocabulary of DEVS model and validating them but also in executing these models by our XML abstract simulator. For each DEVS model, after a schema validation step, we define a simulator that consists of executing a set of XSLT transformations, keeping its traces and generating an XML simulation tree that includes the various transformations that the system has undergone during the simulation time. These transformations are done automatically through our XSLT transformation rules, regardless of the defined DEVS model.
Keywords: discrete event system specification; XML schema definition; extensible stylesheet language transformations; simulation tree; modelling and simulation.
Energy consumption models in dialysis clinics for agent-based decision support
by Stefan Wandler, Shan Bai, Wolfgang Raskob
Abstract: This paper describes an approach to predict the consumptions of water and power in dialysis clinics by simulating the internal processes, on which the impact of power outages is poorly understood. Better understanding is essential to prevent and mitigate adverse health impact on patients. Our methods are based on literature about dialysis process and dialysis clinics, which are always first-hand technical reports instead of academic papers due to the specific research topic. The internal structure of dialysis facilities and its workflow are formulated as the basis of an agent-based modelling approach. The dialysis process is modelled as running different technical systems at different times. The consumption of water and power in each technical system have been implemented mostly in polynomial formula as well as integrals. There are two time schedules as inputs of our models, one of which is for the technical system, regarded as a time-dependent metric, elements of which show the state of the switches of the running technical systems. Switches are represented by 0 (off-state) or 1 (on-state). Usually one patient needs to stay in a dialysis centre over four hours in order to finish one treatment. The time schedule of patients is a time-dependent metric, the elements of which are integers and have limitations due to capacities of different dialysis facilities. The nonlinear models comprise the energy consumption of the technical systems with the time schedules of the running technical system and also the number of patients to be treated. Our model of dialysis clinics will be used as sub-models in an agent-based simulation system aiming to optimise the use of resources in an emergency with power outrages or brownouts. The results presented in this study can be treated as benchmark for decision makers to estimate the performance of a dialysis clinic or centre based on the amount of electricity and water needed and available.
Keywords: critical infrastructures; risk management; decision support; dialysis clinics; agent-based modelling.
Optimisation of customer satisfaction index model for business hall of operator
by Wanru Wang, Xinxiong Liu
Abstract: Business hall plays an important role in a telecom operators service. Modelling the customer satisfaction of the service provided by business hall is beneficial for telecom operators to improve their service quality. The traditional customer satisfaction model is too abstract and general, which makes the satisfaction analysis not precise enough to model the satisfaction index of one specific service. This paper focuses on modelling the customer satisfaction of the service provided by the business hall. An optimisation process on the traditional TCSI model was conducted based on the data acquired from a questionnaire survey. According to the optimised model, suggestions about designing the business hall at the current time are proposed.
Keywords: satisfaction index analysis; model optimisation; design of business hall.
Bed management considering bed-blocking and elective patient admissions using simulation optimization
by Zahra Aghaabdeellahian, Mehdi Bijari
Abstract: Treatment processes in health centres are mostly carried out in such a way that the patient is hospitalized in several parts of the wards during treatment. When patients are obliged to stay in a department until a bed becomes available in the next department, bed-blocking occurs. Hospitals often suffer from the lack of proper planning and ineffective management of hospital beds and medical resources. In this research, we tackle this issue by introducing a multi-objective simulation optimisation model to determine the optimal number of elective admissions, the appropriate number of beds, and the number of patients who are forced to be discharged in each ward. The model minimises hospital costs and the number of patients who are blocked. Owing to the complexity of the issue, two meta-heuristic approaches are developed to solve the model. In this regard, five simulation optimisation algorithms have been implemented to solve the model and compare the results. By solving the presented algorithms, Pareto optimal frontiers are obtained in various states.
Keywords: hospital beds management; bed blocking; multi-objective simulation optimisation; meta heuristic.
Using traffic simulation to quantify performance improvement due to vehicular traffic reduction at a university campus
by Khaled Hamad
Abstract: The purpose of this study is to quantify the benefits of reducing vehicular traffic at a university campus resulting from adopting sustainable transport modes to travel to campus. To this end, a traffic simulation model was developed to estimate improvements in several traffic and environmental performance measures. A total of 11 traffic scenarios were simulated and their results were compared. These scenarios varied from a baseline situation, i.e. the current morning peak-hour traffic, to a variety of traffic-reduction scenarios ranging from 5% to 50% with an increment of 5%. The results showed considerable improvements in traffic flow and air-pollution performance measures. All performance measures witnessed steady improvement as more traffic reduction occurred; nevertheless, traffic measures have seen more improvement as opposed to environmental measures. Statistical significance tests showed that 5% traffic reductions did not show significant impacts on performance, 10% reductions will improve traffic flow, whereas 20% traffic reductions will improve both traffic and air emissions.
Keywords: transportation at university campus; traffic microsimulation; microscopic traffic simulation; environmental impacts; traffic reduction; Sharjah University City.
A seawater RO desalination process driven by dynamic pressure of high-speed seawater droplets
by Hui Lu, Yi Xiang, Qingfen Ma, Mengnan Hao
Abstract: Seawater reverse osmosis (RO) desalination requires driving pressure of 5~8 MPa which is usually offered by the high-pressure pump, the standard device employed in the commercial application, but which presents a series of problems. To replace the high-pressure pump, a seawater RO desalination technique driven by the dynamic pressure of high-speed seawater droplets is proposed. By theoretical calculation and computational fluid dynamics (CFD) simulation, the required operating conditions for the acquisition of effective impacting seawater droplets were investigated. The results showed that the velocity of the seawater droplet should exceed 70 m/s to achieve the driving pressure of 5 MPa, and simultaneously the air flow-rate should exceed 70 m/s to act as the accelerating medium. The proper size of the accelerated droplet at different air flow-rates within the range of 70~100 m/s were determined considering not only the final velocity of the droplets but also their gravitational settling limitation. In addition, five structures of the RO membrane module were designed and tested, in which the ring-shaped and semicircle-shaped structure exhibited good performance with droplet trap rate greater than 90%. Furthermore, the energy balance of the whole system is analysed, and some constructive suggestions are provided to reduce the energy consumption.
Keywords: seawater desalination; RO technique; dynamic pressure; micro droplets.
Simulation-based trajectory tracking coordination of intelligent vehicle with explicit model prediction
by Rufei Xing, Xingyuan Xu, Peng Gong, Weidong Miao
Abstract: One of the main problems for an intelligent vehicle is to address its real-time ability to track the transverse trajectory under multiple constraints. Based on optimisation methodology, this paper proposes a novel algorithm design based on explicit MPC for trajectory tracking. It uses the MPT toolbox, and provides an offline fast solution. Based on the simulation on Simulink/Carsim simulator, it shows that the offline solving method has the same tracking performance as the online solving problem by YALMIP toolbox. The computation speed is significantly increased. This paper has provided a new approach for improving the computation speed of trajectory tracking problem in case of strong nonlinearity and multiple constraints.
Keywords: trajectory tracking; EMPC; vehicle modelling; fast solving.
Middleware for running and debugging Taverna workflows using RESTful web services
by Kasikrit Damkliang, Pichaya Tandayya
Abstract: Scientific workflows composed of independent distributed web services let a user easily orchestrate dataflows and processing tasks, and handle interoperations with ever more intricate workflows. Typically these integrated workflows are complex, tightly-coupled, and computational and data intensive, because of the workflow invocation management. One side effect is the increase in no-response states as unpredictable events and infrastructure inconsistencies interrupt invocations and cause failure, which are hard and heavy work to manually debug. We propose middleware for running and debugging integrated workflows called RDW using the Taverna Server invocation engine which helps the user to investigate complex tightly-coupled workflows. Two debugging modes, sequential and parallel, are provided for inspecting the sub-workflows of these integrated workflows. Also, interactions between the user and the server are orchestrated seamlessly by the RDW, which manages workflow invocations and provides running and debugging logs. The execution time of our RDW is slightly less than the standard Workbench, although the sequential and parallel RDW debugging modes have slightly different running times. RDW offers stable workflow invocation which can significantly reduce the total execution times. The middleware is freely available from our website, http://bioservices.sci.psu.ac.th.
Keywords: invocation management; debugging workflows; result inspection; sequential and parallel debugging; invocation request and handling; scientific workflows; RESTful service.
Staff scheduling in restaurants where hall staff and robots cooperate
by Takashi Tanizaki, Takeshi Shimmura, Nobutada Fujii, António Oliveira Nzinga René
Abstract: The number of companies introducing robots as part of their workforce has been increasing in recent years. One aim of such companies is to have robots perform low value-added work, and humans perform high value-added work. This objective also generally applies to the service industry. Increasing the number of repeat customers and improving profitability are required in the restaurant business. Furthermore, customer satisfaction (CS), employee satisfaction (ES) and management satisfaction (MS) must be simultaneously improved. However, these three indices are in a trade-off relationship. Based on the abovementioned background, this study proposes the modelling of the staff scheduling problem in restaurants, where hall staff and robots cooperate, as a set covering problem. The simulation results show that increasing the utilisation of robots for low value-added work and hall staff for high value-added work with customer contact contributes to improvements in CS, ES, and MS in restaurants.
Keywords: staff scheduling; set covering problem; customer satisfaction; employee satisfaction; management satisfaction.
Occupant counting modelling for intelligent buildings based on data from multiple WiFi sniffers
by Ping Wang, Zhenya Zhang, Qiansheng Fang, Huaqian Cao, Si Chen
Abstract: Space heating, ventilation and air conditioning (HVAC) systems in buildings usually operate in a centralised manner, which relies on building regulation maximum occupancy numbers for maintaining a proper comfort index. In many scenarios, rooms or zones are infrequently used, and may be unnecessarily heated or cooled. Knowing the occupancy information and precise number of occupants in each room or zone can create energy saving through intelligent control of HVAC systems. In this paper, a novel classification-based occupant counting method using multiple WiFi sniffers is proposed firstly to get a coarse estimation of occupancy. Then, to deal with the false negative problem, i.e., those occupants who do not carry a smartphone or the WiFi module is not enabled hence cannot be counted, a p-persistent frequent itemsets with 1-right-hand-side (RHS)-based occupant correction algorithm is further proposed to improve the occupant detection performance in terms of accuracy using association analysis. Finally, our proposed methods are validated through real experiments. Results show that our classification-based occupant detection method using multiple WiFi sniffers outperforms the 1-WiFi-sniffer-based method, and the association analysis based correction algorithm can improve the accuracy performance in that it can see the occupants in buildings that the naive WiFi-based occupant detection method cannot see, which makes it a viable approach to occupant estimation for intelligent buildings.
Keywords: occupant counting; classification; WiFi sniffers; association analysis; frequent itemsets.
Performance modelling and availability analysis of a milk pasteurising system using Petri nets formalism
by Narendra Kumar, P.C. Tewari, Anish Sachdeva
Abstract: The focus area of this work is integrating Reliability, Availability, and Maintainability (RAM) aspects into the conceptual process design of a real industrial system. Quantitative performance analysis has been carried out using a Petri Nets (PN) approach. In the present study, availability is considered as a performance measure which has been used as an indicator of the reliability and maintainability of the plant. The availability is considered in the process design stage for sorting different design alternatives. The proposed technique suggested provides a better way of understanding behaviour of a system under various operating conditions. It will also help practitioners in deciding on maintenance strategy so that operation and maintenance costs can be optimised. Stochastic Petri Nets (SPN) has been used to model the possible interactions among all active or parallel equipments in the system. Performance parameters have been evaluated using modelling and simulation software GRIF of Petri module.
Keywords: failure; RAM tools; Petri nets; performance modelling.
Special Issue on: ISSPM 2018 Integrating Nodes and Optimisation across Social and Scientific Areas in Sustainability Loops
Error of single-phase proton exchange membrane fuel cell model based on Brinkman-Darcy's law in different flow fields
by Shizhong Chen, Zhongxian Xia, Xuyang Zhang, Yuhou Wu
Abstract: Proton exchange membrane (PEM) fuel cell is an auspicious energy device for the future with high energy efficiency and zero emissions. PEM fuel cell performance can be improved by optimising the flow field using numerical models based on Brinkman-Darcy's law. However, errors made by applying Brinkman-Darcy's law cannot be avoided; errors should be carefully investigated for different flow fields. In this paper, a single-phase PEM fuel cell model based on Brinkman-Darcy's law was developed, considering the effects of flow field on both local electrochemical active area (ECA) and effective permeability. The results showed that the model well predicted the performance of the flow field with a high resolution land width, such as 1 mm, but it over-estimated the performance under the low voltage region when the land width was 2 mm or larger, since the high mass transfer loss was under-estimated by the model.
Keywords: Brinkman-Darcy's law; flow fields; under-land cross-flow; proton exchange membrane fuel cell.
Dynamic performance of high supporting formwork under horizontal impact load
by Zhengran Lu, Maosheng Zhang, Chao Guo
Abstract: Dynamic performance of a high full-scale supporting formwork (HSF) subjected to horizontal impact loading was examined. It could be concluded that transverse X-bracings in the horizontal impact load direction have a more significant effect on the bearing performance and dynamic characteristics of an HSF than longitudinal X-bracings. An increase in the amount of poured concrete and the failure of the X-bracings reduces the natural frequency of the HSF. With the gradual increase in the amount of poured concrete, the maximum dynamic axial force of posts may increase from 4.33 kN to 12.77 kN under different X-bracing conditions during concrete placement. With failure of some main nodes, any impact load significantly increases the axial force acting on the posts. Dynamic axial force acting on some of the posts can increase by as much as 120% if 5% of fasteners fail during concrete pouring compared with that when all fasteners and X-bracings are intact.
Keywords: high supporting formwork; horizontal impact load; dynamic performance; experimental research.
Cloud resource orchestration optimisation based on ARIMA
by Hua Qin, Min Yu, Yingxu Lai, Zenghui Liu, Jing Liu
Abstract: The problem of resources management in the cloud environment, focusing on the platform as a service (PaaS), satisfying the demands of users, and relieving the load on the server in high concurrency, requires attention. After analysing the resource orchestration technology on PaaS, this paper presents a dynamic orchestration optimisation framework based on autoregressive integrated moving average model (ARIMA) model. The architecture is based on an OpenStack infrastructure as a service (IaaS), and combines with Cloudify, a resource orchestration software on the PaaS. Adjustments may be made in advance by predicting the resource consumption in the next time period. Experiments showed that this architecture can effectively shorten the concurrent response time and improve the utilisation of memory.
Keywords: Cloudify; OpenStack; cloud computing; orchestration.
Morphological component analysis based on mixed dictionary for signal denoising of ground penetrating radar
by Jianhua Zhang, Haohao Zhang, Yang Li, Xueli Wu
Abstract: Forward modelling is applied to simulate the ground penetrating radar (GPR) detection environment, and a modified morphological component analysis (MCA) algorithm is applied to GPR signal denoising. Finite-difference time-domain (FDTD) method is used to perform finite difference approximation to the space and time derivatives of Maxwell's equations. Under the forward simulation framework, the MCA algorithm applies a sparse dictionary to decompose the GPR signal. However, clutter is not represented as there is no corresponding sparse dictionary, the clutter is removed when the signal is reconstructed. The core of the MCA is to select a suitable dictionary. The combination of undecimated discrete wavelet transform (UDWT) dictionary and curvelet transform dictionary(CURVELET) is selected. The improved MCA algorithm is compared with singular value decomposition (SVD) and principal component analysis (PCA), to confirm the high performance of the proposed algorithm.
Keywords: finite-difference time-domain; FDTD; signal processing; morphological component analysis; MCA; undecimated discrete wavelet transform; UDWT; CURVELET; ground penetrating radar; GPR.
A data cleaning method for water quality based on improved hierarchical clustering algorithm
by Qingxuan Meng, Jianzhuo Yan
Abstract: Identifying and rectifying incomplete water quality data is of vital importance. A data cleaning method based on improved balanced iterative reducing and clustering using hierarchies (BIRCH) clustering algorithm is proposed. The clustering feature tree of water quality data is constructed and the cluster vector of the clustering feature tree is obtained by the agglomerative method. The optimal cluster number is determined according to the Bayesian Information Criterion and the nearest clustering ratio. The Pauta criterion is used to detect the global outlier and artificial neural network (ANN) is used to fill in outliers and missing values. Finally, the improved data cleaning method is applied to water quality monitoring data of Beijing wastewater treatment plant. The experimental results show that the data cleaning method can not only detect abnormal values and missing values accurately, but also normalise and complete missing data.
Keywords: outliers; water quality monitoring; multivariate data; clustering; artificial neural network; ANN.
Photovoltaic maximum power point tracking based on IWD-SVM
by Wenqing Zhao, Yayun Meng
Abstract: Photovoltaic system maximum power point tracking (MPPT) has great potential for improvement of power generation. To optimise MPPT, this paper presents a prediction model based on an intelligent water drops optimisation support vector machine (IWD-SVM) for maximum power point working voltage. The Intelligent Water Drops (IWD) algorithm is used to optimise the penalty factor and kernel function parameters of the SVM, thus improving the training efficiency of the learning machine. Based on the optimisation algorithm, the SVM is used to model the PV array, the prediction results are compared to verify the accuracy and effectiveness of the IWD-SVM model. In addition, the IWD-SVM model is compared with the traditional neural network prediction results, which further verifies the validity of the proposed IWD-SVM model.
Keywords: IWD model; photovoltaic array; support vector machine; maximum power point tracking; neural network.
Simulation of multilateration system based on Chan algorithm and conjugate gradient optimisation algorithm
by Jianhua Zhang, Feng Gao, Yang Li, Xueli Wu
Abstract: In multilateration (MLAT) systems, the traditional Chan algorithm applies the theory of time-difference-of-arrival (TDOA) to solve the target position of the mathematical model. By introducing intermediate variables, the algorithm adopts a two-step weighted least-squares solution. The introduction of intermediate variables results in the target position equation producing a fuzzy solution, this reduces positioning accuracy. The conjugate gradient algorithm (CGA) is one of the most useful methods for solving large linear equations, it avoids solving the inverse of the matrix, whilst it 'speeds up' the solution of the target position. A four stations multi-point-positioning system mathematical model is established, and a new fusion algorithm Chan-CGA is applied to the MLAT system. Finally, the fusion algorithm is evaluated by simulation and compared with the Chan-Taylor algorithm.
Keywords: multilateration; time-difference-of-arrival; Chan algorithm; conjugate gradient optimisation algorithm.
Special Issue on: ISSPM 2018 Internet of Things and Smart City Technologies
A DT-CWT-based infrared-visible image fusion method for smart city
by Guanqiu Qi, Mingyao Zheng, Zhiqin Zhu
Abstract: Following the development of smart city, informative images play a more and more important role in recognition, detection, and perception. As an efficient way, image fusion technique integrates information from multiple images. Multi-scale transform (MST) and sparse representation (SR) are widely used in infrared-visible image fusion. Traditional MST-based fusion methods are difficult to represent all features of source images. At the same time, traditional SR-based fusion methods do not consider morphological information of image features in dictionary learning processes. To overcome the defects of both MST- and SR-based fusion methods, this paper presents a infrared-visible image fusion framework by combining double-tree complex wavelet transform (DTCWT) and SR. The source images are decomposed and clustered into high- and low-pass bands by DTCWT. The high-pass bands are fused by the Sum Modified Laplacian (SML). The low-pass bands are fused by the SR-based approach. The fused high- and low-pass bands are integrated and reconstructed by DTCWT to form the final fused image. Comparing with five mainstream image fusion solutions, the proposed fusion framework can achieve state-of the-art performance in infrared-visible fusion images.
Keywords: DT-CWT; sparse representation; SML; infrared-visible; image fusion.
A two-level identification model for selecting the coordination strategy for the urban arterial road based on fuzzy logic
by Haochen Sun, Feng Qiao, Lingzhong Guo, Zhaoyan Wang
Abstract: A novel model for identifying the traffic condition of urban arterial roadways is proposed in this paper to improve the operational efficiency and safety of the urban traffic arterial road system. During the identification process, fuzzy analytic hierarchy process and fuzzy integrated evaluation are employed to identify the traffic condition on the arterial road; according to the fuzzy logic scheme, a proper coordination strategy is then generated based on the resulting identification of each way of the artery. To verify the effectiveness of the proposed method, a numerical experiment is carried out by using the microscopic traffic simulation software VISSIM, where a traffic flow simulation system is generated according to the real-time traffic data. The comparison results show that the proposed model works well to fit with the actual operating condition of the arterial traffic and the proposed coordination strategy can provide a better performance for the traffic management.
Keywords: traffic condition identification; coordination strategy; urban arterial road; fuzzy logic.
Research on optimal collaborative method for microgrid environmental and economic dispatch in grid-connected mode
by Juan Chen, Bin Lu, Lingling Hao
Abstract: In recent years, real-time optimisation of microgrid dispatch with minimal total costs of energy generation and emission has been an urgent problem. In this paper, a collaborative method is considered for microgrid connected mode. At first, we construct the microgrid schematic diagram of energy flow. Then, a mathematical model is presented for dispatch optimisation environmentally and economically. After we define the objective function according to the energy consumption, maintenance and systemic carbon emissions, two types of constraint are given, including the single input-output balance and the overall energy flow balance. Thirdly, we analyse the cooperative co-evolutionary genetic algorithm and apply it to a large number of cases. The better optimisation performance and convergence rate are obtained by comparing the method with the traditional genetic algorithms. The experimental results show it may play a significant role to the optimal scheduling of distributed energy generations in the grid-connected mode.
Keywords: optimal method; collaborative method; microgrid; environmental dispatch; economic dispatch; connected mode; optimisation; genetic algorithm; energy generation; emission; distributed energy.
An improved artificial fishes swarm algorithm for traffic signal control
by Yang Wang, Qiang Wang, Bin Lu
Abstract: The excessive growth of car ownership has caused great pressure on urban traffic. The traffic congestion is the most acute problem. One of the main causes of traffic congestion is the unreasonable scheme of traffic signal timing at road intersections. In view of the limitation of the Webster algorithm, we combine the artificial fishes swarm algorithm, chaos search and feed back strategy based on the optimisation theory of the signal timing to solve this problem. Furthermore, we apply the algorithm to the field of the traffic signal control. We set the average of vehicle delays and parking numbers as the target and improve the target road intersection timing scheme by using the optimisation algorithm. This method enhances the capacity of the target intersection effectively. Taking the condition of the target road intersection and the basic data into consideration, we construct the simulation model of the road intersection through the VISSIM simulation modelling tool. Then we import the relevant data and obtain a new timing plan, which sets a new cycle and the green light duration of each phase. Compared with the original method, the algorithm based on the artificial fish-swarm is feasible and effective.
Keywords: artificial fish swarm algorithm; road intersection; traffic light control; signal timing; VISSIM simulation.
Simulation and analysis of user-side transaction technology for energy blockchain considering multi-chain structure
by Guping Zheng, Jingya Hu, Gang Li
Abstract: Blockchain advantages, such as decentralised tamper-proof and smart contracts, are naturally suitable for the trading needs of the Energy Internet, dealing with the problem of low efficiency, waste of resources, privacy leakage, etc. In this paper, an energy trading method is proposed based on blockchain expansion technology. The lightning network is used to expand the blockchain trading process, and divides the transaction into on-chain trading and off-chain trading; and the chain structure of the energy blockchain is expanded using a multi-chain architecture, and the blockchain is divided into an account blockchain and a transaction blockchain. A case study is carried out, in this research work, in combination with multiple energy trading scenarios in the energy local area network. The results show that the proposed method possesses a significant performance of improving the efficiency of energy trading and reducing the complexity of trading information.
Keywords: blockchain; Energy Internet; energy trading; energy blockchain; lightning network; multi-chains; off-chain trading.
WLAN indoor positioning method based on gradient boosting and particle filtering
by Libin Hu, Zhongtao Li
Abstract: Indoor positioning technology has shown its great application prospects in smart cities. The main purpose of this paper is to study a low-cost, low-error indoor positioning method that can get a accurate indoor position when communicating with Wireless Local Area Networks (WLAN). The paper optimises the traditional WLAN indoor positioning method based on location fingerprint database, and algorithms about indoor signal simulation, similarity matching of vector and continuous positioning are tested. The WLAN indoor positioning method based on gradient boosting and particle filtering is proposed. The paper finds the indoor positioning result with an average error of 1.7 metres, which verifies the feasibility of WLAN indoor positioning and shows that the positioning accuracy will be improved with the further optimisation of the positioning method. The potential application values of WLAN technology make it more convenient for Internet of Things technology.
Keywords: IOT-SCT; gradient boosting; particle filter; WLAN indoor positioning.
iCampusGuide: a multi-purpose guide system in the intelligent campus
by Chunyan Yu, Hui Qi, Haibao Chen, Shenghui Zhao
Abstract: As an important application of intelligent campus, Campus Guide aims to help visitors get to their destination. In this paper, a flexible and low-cost campus guide model named iCampusGuide is proposed, which generalises the problem of university campus guide including objective, constraints, system and algorithms. The proposed iCampusGuide provides visiting reservation, route navigation, parking guideline and broadcasting introduction of buildings during the navigation. Technically, iCampusGuide adopts ibeacons for accurate location and navigation, and provides the parking suggestion by sending real-time snapshots from the parking lot nearest to the destination. Particularly, iCampusGuide provides business mode, tour mode, driving mode, and walking mode for different purposes. Each mode uses different route navigation algorithms. To verify the model, a client-server software is developed and implemented in a real university campus. Experiments show that the model is effective.
Keywords: intelligent campus guide; beacon; intelligent campus; intelligent parking.
Modelling of traffic capacity under traffic accident
by Ling Yu, Yi Tong Zhang, Si Yu Jia
Abstract: In this paper, the traffic characteristics of an urban road under traffic accidents is analysed from three aspects: the traffic volume characteristics, the definition of accident sections and the evolution characteristics of traffic capacity. On this basis, the theoretical analysis of road traffic capacity under traffic accidents is carried out, and a capacity model is established. Guided by traffic volume theory and lane-changing rules, the correction coefficients of various influencing factors are simulated by adjusting the parameters on VISSIM, and the results are used to analyse the influencing factors of traffic capacity under traffic conditions. The curve fitting of the obtained data was conducted by Matlab, a regression model of the reduction factor of traffic capacity of urban roads under traffic accident and each influencing factor and the actual traffic capacity model are built. Taking the traffic accident on an urban road as an example, quantitative analysis is made of the traffic capacity of an urban road under the traffic accident to verify the proposed model, and the results show its effectiveness.
Keywords: urban road; traffic accident; actual traffic capacity; PTV-VISSIM.
Special Issue on: ISSPM 2018 Theory, Methodology and Application of Modelling and Simulation
Modelling and application of laparoscopic simulation system for panhysterectomy
by Xue Wang, Lili Xuan, Ying Pan, Haoying Wang, Xiaochen Huang, Ming Liu
Abstract: The laparoscopic surgery simulation training system uses human anatomy visual reproduction and force-feedback technology, and uses a variety of medical image data on the computer to establish a virtual environment with vision, hearing, speaking, dynamic, smell, feel, and touch. Surgeons conduct surgical training in the virtual environment, which includes suture, knotting, hand-eye coordination, organisational separation, and directional adaptation. In this paper, the issue of simulation-based training with the laparoscopic simulation system is dealt with for training of internship surgeons in panhysterectomy. The model is built and the practical training results are analysed and compared for the performance of two groups of internship surgeons under model-based training and conventional training, respectively. The results show that there was no significant difference in total abdominal hysterectomy (TAH) and crossover test for the two groups, whereas practice test scores increased significantly (p < 0.05), with the group using the model of laparoscopic simulation system scoring higher than the other group. It proves that the laparoscopic simulation system application in gynaecological surgery will help to improve the clinical skills of internship surgeons. The advanced simulation system makes a great contribution to reducing medical accidents, adding to the progress of surgery and its training.
Keywords: laparoscopic simulation system; panhysterectomy; laparoscopic surgery; medical modelling; clinical skill.
Seamless development in Java of distributed real-time systems using actors
by Franco Cicirelli, Libero Nigro, Paolo F. Sciammarella
Abstract: The work described in this paper is concerned with a model-driven development of distributed real-time systems, such as cyber-physical systems. One challenge in such systems development consists of ensuring that a final implementation is compliant with its model used for functional and temporal property checking. In particular, a modern Java framework called Theatre is described, which enables the modelling, analysis and synthesis of distributed real-time systems in a way that preserves such compliance. Theatre is based on the paradigm of actors, that is, highly modular and encapsulated software entities that communicate each other by asynchronous message-passing. Theatre rests on lightweight actors regulated by a customisable reflective control layer. Key features of Theatre are its support to seamless application development and timing predictability. The same model can be developed, without distortions, from early analysis through design and to a series of implementations. The paper describes Theatre and demonstrates its application to the development of a distributed dependable real-time system. Modelling, property checking by simulation and real-time prototyping are all illustrated. Theatres current level of maturity and practical implementation in Java are detailed.
Keywords: distributed timed actors; Java; modelling and simulation; timing constraints; seamless development.
Simulation modelling and analysis of balance mechanisms of innovation search in innovation networks
by Linling Xie, T.I.E. Wei
Abstract: Based on the scale-free weighted dynamic network, this paper proposes an agent-based model to investigate the dynamics characterising the interaction between balance mechanisms of innovation search and the innovation network. Specifically, it explores how two balance mechanisms of innovation search, punctuated equilibrium and ambidexterity, influence the evolution of the growth of network knowledge and performance through the simulation of the three-stage innovation search processes in the innovation network. In addition, it considers and assesses the impact of the rate of knowledge diffusion. The results show that the balance mechanisms of innovation search and the innovation network are co-evolutionary. The balance mechanisms of innovation search have an impact on the growth of network knowledge and performance, and the rate of knowledge diffusion has a contingent effect. This study provides a valid theoretical analysis framework and approach for future research in balance mechanisms of search.
Keywords: balance mechanisms of innovation search; innovation network; agent-based simulation; network evolution.
Research on NOx emission of coal-fired unit based on multi-model clustering ensemble
by Chenggang Zhen, Huaiyuan Liu, Hanyong Hao
Abstract: The predictive control of NOx emission generated by coal-fired units has an important impact on the economic benefits of a power station and control of environmental pollution. In order to enhance the accuracy of the prediction model, a modelling method of boiler NOx emission based on Voting Multi-model Soft Clustering (VMSC) ensemble is proposed. The data space is divided into three subspaces according to the level of NOx emission, and the variables that participate in clustering are determined by using variable weight based on relevant analysis and hierarchical clustering using information entropy. The proposed algorithm VMSC is used to obtain a new membership degree matrix of each subspace. The multiple Least Squares Support Vector Machine (LSSVM) models of each subspace are compromised by the least-squares method fused membership degree. The simulation results show that the VMSC algorithm, which merges Soft Fuzzy C-Means clustering (SFCM) and Genetic Algorithm-Soft Fuzzy C-Means clustering (GA-SFCM), improves the accuracy of clustering, and the simulation performance is better than other selected models. The integrated model VMSC-LSSVM can achieve accurate prediction for NOx emission of the utility boiler and effectively solve the problem that the model uses a single method to model is a weak generalisation.
Keywords: prediction of NOx emission; soft clustering; cluster ensemble; SFCM; GA-SFCM; multi-LSSVM; ensemble model;.
Decision support for ship collision avoidance in the narrow channel
by Yuanqiang Zhang, Guoyou Shi, Hu Liu, Weifeng Li
Abstract: To solve the problem of ship collision avoidance in restricted waters, a method is proposed, in this paper, for obtaining the Time to the Closest Point of Approach (TCPA), the Distance to the Closest Point of Approach (DCPA) and the meeting position considering multileg route, proposed method considers the turning position and turning time of the ship. For ships with a collision risk, a safe speed can be obtained by setting a new meeting position. The safe speed considers the time elapsed for altering speed. At the end, the proposed method is used to get the collision risk and avoidance measures for three different encounter situations. A navigation simulator is used to verify the avoidance measures. The experimental results show that the proposed algorithm can obtain more accurate results than the existing algorithms.
Keywords: restricted waters; waters intersection; TCPA; DCPA; ship collision avoidance.
Modelling and simulation of intelligent collision avoidance based on ship domain
by Weifeng Li, Jiaxuan Yang, Xiaori Gao, Jiagen Yu
Abstract: Intelligent collision avoidance systems can increase the safety of ship navigation and reduce the influence of human error. Thus, related technologies are critical to the development of the world's shipping industry. Risk of collision is a central concept in the Convention on International Regulations for Preventing Collision at Sea, 1972 (COLREGs). Collision risk is also a key factor in determining whether a collision avoidance action is required, specifically with regard to intelligent collision avoidance decisions. On the basis of the ship domain proposed by the Fujii, at first, this paper defined the risk of collision index λ, which can be used to measure the risks between owe ship ant the target ships, then, according to the COLREGs, categorised ship encounter types as head-on situation, crossing situation, and overtaking situation, and established the action flow charts of each of these situations, at last, With the permission of Dalian Maritime University, the training ships Yu Peng and Yu Kun were selected as simulation objects, the paper presented simulations of head-on, crossing and overtaking situations to verify the usability of the proposed models.
Keywords: simulation; modelling; ship; intelligent collision avoidance; risk of collision; ship domain.
Validating trustworthy service composition through VIPLE and pi-calculus
by Shenghui Zhao, Yuemin Li, Yang Wang, Yinong Chen
Abstract: The current formal verification practice focuses on functionality and does not consider the non-functional attributes verification. In this study, we propose a method in which non-functional attributes are incorporated into the logic rules of inference in terms of composition of the linear logic and pi-calculus. Giving credibility to non-functional attributes is important, especially in the cloud computing platform and IoT environments, where trust and security are ultra-important. Such studies have not been paid much attention by researchers and practitioners. In our approach, the evolvement of the non-functional attributes are included in the process of formal verification of the service composition scheme. In addition to theoretical analysis, we applied a tool named VIPLE (Visual IoT/Robotics Programming Language Environment) to execute and verify the validity of the service composition model's function. We translate the proving process of the linear logic into the corresponding pi-calculus expressions. VIPLE can translate visual work flow into pi-calculus and can verify the correctness of pi-calculus expressions.
Keywords: formal verification; pi-calculus; service composition; visual programming; VIPLE.
Modelling of ship collision avoidance behaviours based on AIS data
by Miao Gao, Guoyou Shi
Abstract: The original automatic identification system (AIS) data are so large that they cannot be directly applied to learning and training, so the collision avoidance data must be filtered, identified, and extracted. AIS data from the Laotieshan channel are used as raw data to identify successful cases of collision avoidance. Ship navigation statuses are screened according to AIS message codes. The improved density-based spatial clustering of applications with noise algorithm (DBSCAN) is used to cluster the four types of habitual route of ship trajectory, with the rest of the data as candidate data for ship matching. Ship encounter situations are planned for 13 categories considering the ship light arc range and the requirements of the International Regulations for Preventing Collisions at Sea (COLREGs). The matched data use a sliding window algorithm for extracting ship navigation behaviour, which is then stored in the form of segmented ship trajectory unit sequences. This study suggests a new knowledge base of intelligent ship collision avoidance data, providing a novel method and theoretical guidance for future developments in ship collision avoidance methods.
Keywords: USV; ship collision avoidance; modelling; AIS; big data; extraction of behaviour feature; ship trajectory unit.
Real-time health status evaluation for electric power equipment based on cloud model
by Wenqing Zhao, Min Cui
Abstract: The health status evaluation of electric power equipment is an important issue with extensive concerns in power system communities around the globe. In consideration of the uncertain characteristics of the monitoring data of wind turbines, a real-time health status evaluation method for wind turbines is presented employing the advantages of the cloud model in dealing with uncertain information. In the presented method, real-time data are analysed based on the well-established unsupervised clustering to partition the operational space. The health evaluation model is then trained based on the cloud model and cloud transformation, combining with SCADA historical state data and fully considering the uncertain information of wind turbines. The proposed model is applied to evaluate the health conditions of a 1.5 MW wind turbine located in northern China, and it is demonstrated that this model can detect the changing trend, and hence to promote reliability of wind turbines, and reduce maintenance costs.
Keywords: electric power equipment; cloud model and cloud transformation; health evaluation; unsupervised clustering.
Fast fractal image retrieval algorithm based on HV partition
by Hejin Yuan, Mingjie Li, Weihua Niu, Linna Zhang, Kebin Cui
Abstract: Existing quadtree-based fractal algorithms and fractal algorithms based on Horizontal Vertical (HV) have the problems of long encoding time and low accuracy in the task of image retrieval. In this paper, an improved fast fractal image retrieval algorithm based on HV segmentation is proposed, which speeds up the coding time and improves the accuracy for real-time searching. In order to improve the coding efficiency, the proposed algorithm restricts R block segmentation to certain direction and location in the coding phase and uses the local codebook to find the optimal matching of the partitioned blocks. We also introduce a weighting equation calculating method of area intersection to the image matching. New weighting parameters with respect to the sizes of partitioning blocks are proposed to improve the accuracy of image retrieval. The constraint-based HV segmentation algorithm and the local codebook matching strategy are tested on the texture and Olivetti Research Laboratory (ORL) face datasets. The experimental results show that the proposed algorithm accelerates the speed of image encoding. When the recall ratio is 100%, the precision of our algorithm has improved significantly. The proposed algorithm based on HV segmentation outperforms traditional fractal search algorithms in terms of adaption adaptivity.
Keywords: HV segmentation; fractal coding; precision; image retrieval.
Large-scale text classification with deeper and wider convolution neural network
by Min Huang, Wei Huang
Abstract: The dominant approaches for most Natural Language Processing (NLP) tasks such as text classification are recurrent neural networks (RNNs) and convolutional neural networks (CNNs). These architectures are usually shallow and only have one or two layers, which cannot easily extract inner patterns in natural language. Different from the original feature of image pixels with regularity, words and phrases are highly abstracted from human knowledge without direct correlation. Shallow models only capture the surface relation between them while deep models cannot directly apply to them. Therefore, a Shuffle Convolution Neural Network (SCNN) is proposed to address the shallow learning problem by introducing wider inception cell and deeper residual connection. In the paper, the difficulty of applying deep models to NLP problems is overcome by tricks of shuffling channel input and reshaping the output dimension in first layer. The results of the experiments carried out in this research work demonstrate that the proposed SCNN makes a great improvement in accuracy and efficiency compared to shallow models.
Keywords: text classification; shuffle channel; inception cell; residual connection.
Parameter co-evolution mechanism of particle swarm optimisation algorithm
by Ming Zhao, Xiaoyu Song, Yichen Gao
Abstract: PSO (Particle Swarm Optimisation) algorithm is a kind of evolution optimisation algorithm, which simulates the intelligent behaviour of birds foraging. The running parameters are the important factors that influence the performance of PSO, and the optimisation of the fixed setting and the adjustment mechanism on them is one of the hot research directions for the improvement of PSO. Based on the related research, this paper designs the co-evolution mechanism for the parameters, including both inertia weight and accelerating factors, which defines the stochastic evolution speed to reflect the current state of population evolution during the iterative process, and uses it as feedback to set the inertia weight and the two accelerating factors. PSO with the parameter co-evolution mechanism can realise cooperative evolution of the running parameters with the population by dynamically adjusting parameter values according to the population evolution state. Finally, compared with five widely recognised parameter fixed settings or adjustment mechanisms, on 20 optimisation benchmark functions of different categories, the effectiveness and the efficiency of the proposed mechanism are verified based on indicators including success rate, solution quality, stability and convergence speed.
Keywords: particle swarm optimisation; parameter co-evolution; inertia weight; accelerating factor; adjustment mechanism; stochastic evolution speed.
Special Issue on: ISSPM 2018 Modelling, Simulation and Optimisation of Manufacturing and Production Processes
Modelling and implementation of an intelligent stowage simulator for container ships
by Qingwu Wang, Jian Zhao, Lin Ma
Abstract: To solve the problems that conventional loading master for container ships merely provides the stability, strength, floating condition, etc., a comprehensive intelligent simulator was worked out, which can also obtain the amount of restowage containers, verify segregation scheme for dangerous containers, etc. The BLOCK algorithm was proposed for the first time for restowage problems with respect to the containers on deck jam that in hold and all in hold or on deck. In the case of all in hold or on deck, independent stowage and mixed stowage were studied in some detail. A fast and effective algorithm was also put forward to perform the segregation verifying. The proposed algorithms were verified by the loading condition from the loading manual.
Keywords: container ship; intelligent stowage simulator; restowage; container segregation.
An optimised steelmaking-continuous casting scheduling simulation system with Unity 3D
by Liangliang Sun, Yaqian Yu, Li Zhang, Tingting An
Abstract: This work considers the transportation time involved in ladle allocation during the steelmaking-continuous casting production. The optimisation problem of equipment allocation is presented, the optimal production sequence is determined, and a schedule for charges is determined. In order to ensure that the operation time and the energy consumption are minimised, a solution methodology combining a heuristic algorithm and a conflict elimination algorithm is developed. A two-stage heuristic algorithm is used to solve the problems of steel leakage continuous casting, equipment idling, and equipment overload, which improves the logistics of clogging and shortens the waiting time of charges. Then a conflict elimination algorithm is presented to solve the conflicts that may exist among charges and realise the optimisation of a rough scheduling plan. The simulation experiment based on actual production data shows that this methodology can effectively solve the steelmaking and continuous casting scheduling problem. To validate the scheduling plan more intuitively and modify it further, we present an optimisation system based on Unity 3D simulation platform. The 3D model of ladle, converter, refining position and caster made by 3ds Max is imported into Unity 3D engine and renders a reasonable distribution. The system can effectively evaluate the optimisation of the solution and adjust the related data to modify the scheduling plan and ultimately get a reasonable rescheduling plan.
Keywords: steelmaking-continuous casting; production scheduling plan; conflict elimination algorithm; heuristic algorithm; Unity 3D.
Test and effect analysis of hydraulic automatic pressure regulating water injection device in Shengli Oilfield
by Yuhai Cui, Jiehua Feng, Dongya Zhao
Abstract: In the later stage of oilfield exploitation, owing to the decrease of fossil oil, the oil recovery of the oilfield will be reduced, and the production may even be stopped. In order to stabilise the production of the oilfield, it is an effective measure to develop the oilfield by water injection. Therefore, it is very important to study the pressure-regulating water injection technology, and the hydraulic automatic regulating device is the key. In this paper, a set of hydraulic automatic pressure-regulating water injection devices has been developed, which mainly includes three parts: screw motor module, screw pump module, and transmission device between screw motor output shaft and screw pump input shaft. The shunt injection of each layer can be realised without deployment by the automatic pressure-regulating device. The change of total water injection volume can automatically adapt to the reservoirs according to the flow distribution ratio. At the same time, the test and field experiments in Shengli Oilfield, Dongying, China, show that the developed device has good energy-saving effects.
Keywords: Shengli Oilfield; regulating device; energy use; application effect.
A study of flexible flow shop scheduling problem with variable processing times Based on improved bat algorithm
by Jianyong Bian, Liying Yang
Abstract: In order to solve the problem of flexible flow shop scheduling with variable processing time (FFSP-VPT), a mathematical model is established, in this paper, based on analysing the processing time selection, defect detection, and rework of jobs with variable processing time. According to the characteristics of FFSP-VPT, a two-stage coding method is designed using ranked over value (ROV) coding. Based on the Bat Algorithm (BA), a self-adaptive elite bat algorithm (SEBA) is developed as the global optimisation method by using Hamming distance-based elite individual set and adaptive position update. Crossover tests are designed to determine the optimal values of critical parameters in SEBA. Validity of SEBA on solving FFSP-VPT in actual production is verified by comparing the simulation test results of SEBA with those of other algorithms.
Keywords: flexible flow shop; bat algorithm; variable processing time; Hamming distance; adaptive position update.
Bus manufacturing workshop scheduling method with routing buffer
by Zhonghua Han, Jingyuan Zhang, Shiyao Wang, Yuanwei Qi
Abstract: Aiming at solving the problem that the moving route is complicated and the scheduling is difficult in the routing buffer of the bus in the manufacturing workshop, a routing buffer mathematical programming model for bus manufacturing workshop is proposed. We design a moving approach for minimising the total setup cost for moving in routing buffer. The framework and the solution of the optimisation problem of such a bus manufacturing workshop scheduling with routing buffer are presented. The evaluation results show that, compared with the irregularly guided moving method, the proposed method can provide a better guideline for the bus movement in the routing buffer by reducing the total setup time of all buses processed at the next stage, and a better scheduling optimisation solution that minimises the maximum total completion time.
Keywords: bus manufacturing workshop; flexible flow shop scheduling; routing buffer; moving method.
Special Issue on: ICSCIB 2018 Green Progression in Smart Cities and Intelligent Buildings
Deep activity recognition in smart buildings with commercial Wi-Fi devices
by Qizhen Zhou, Jianchun Xing, Yuhan Zhang, Qiliang Yang
Abstract: Activity recognition acts as a key enabler of smart building applications, such as behaviour analysis, health diagnosis and user authentication. However, existing methods require either burdensome equipment, or light and Line-Of-Sight (LOS) working conditions. To address this challenge, we propose DeepAR, a device-free human activity recognition system with prevailing Wi-Fi signals, which circumvents the use of dedicated devices. DeepAR mainly exploits two key techniques to recognise human daily activities. Firstly, a novel principle component extraction method is presented to capture the motion-induced distortions and discard the irrelevant interferences. Secondly, deep feature maps are constructed with time and frequency domain characteristics, and a deep Convolutional Neural Network (CNN) model is further applied to classify the activity labels. DeepAR is implemented with commercial Wi-Fi devices, and the performance is evaluated through extensive experiments. Experiment results show that DeepAR can achieve an average accuracy of 98.6% in a meeting room and 96.4% in a student office.
Keywords: channel state information; wireless sensing; deep learning; principle component analysis; smart building.
Fault diagnosis and location method for electrical power supply and distribution of buildings
by Jundong Fu, Tianhang Leng
Abstract: This paper presents a new fault diagnosis and location method for electrical power supply and distribution of buildings using Bayesian and Wavelet Neural Network (WNN). Aiming at the complex trunk-type power supply and distribution structure of buildings, wavelet transform (WT) is adopted to process the current, voltage and phase data of each branch to extract the features that can distinguish faults effectively. A fault diagnosis model based on Bayesian network is established by the above features. In order to improve the accuracy of WNN in fault location in buildings, a WNN method optimised by dragonfly algorithm (DA) is proposed to obtain better thresholds and weights, which are used to enhance the prediction ability. A simulation study was made with Matlab/Simulink to verify the performance of the proposed method on a power supply and distribution model.
Keywords: fault diagnosis and location method; electrical power supply and distribution of buildings; wavelet transform; Bayesian network; wavelet neural network; dragonfly algorithm.
Energy management of microgrid based on day-ahead and short-term optimisation
by Xiaohui Wang, Yiming Zheng
Abstract: Microgrid is an effective way to accept distributed renewable energy. However, owing to the uncontrollable and intermittent nature of renewable energy, coupled with the complex operational modes of microgrid, the scheduling of microgrid is more difficult to optimise and control. So it has become a key issue to optimise the coordinated operation of distributed generation units, energy storage devices and loads in energy management of microgrid. In order to guarantee the stable operation, an optimisation scheduling strategy with multiple time scales is proposed in this paper. Based on an independent microgrid, the output power of the equipment units in the microgrid are modelled and the objective functions and constraint conditions are determined. A day-ahead and short-term optimisation scheme is carried out, and the optimal scheduling program and combination of each distributed generators are optimised by the particle swarm optimisation (PSO) algorithm. The simulation results are analysed and summarised to verify the feasibility and validity of the proposed optimisation strategy.
Keywords: microgrid; energy management; multiple time scales; PSO; day-ahead optimisation; short-term optimisation.
Arancino.cc(TM): an open hardware platform for urban regeneration
by Maurizio Giacobbe, Francesco Alessi, Angelo Zaia, Antonio Puliafito
Abstract: The term 'metabolism' is generally used to define the set of chemical processes that occur within a living organism in order to maintain its life. Based on this definition, by analogy, we use the 'urban metabolism' concept to show the life of a city. Urban metabolism can be analysed and therefore its status evaluated (e.g., optimum, good, insufficient, etc.) based on measuring specific parameters (i.e., environmental temperature, humidity, pressure, quality of the air). Nowadays, although both technical and scientific literature present a multitude of methods, techniques and approaches concerning the monitoring and control of environmental parameters, the technological evolution requires a continuous updating of the same literature, as well as a regulatory adaptation. A city, in fact, is a set of very complex processes whose activities involve worldwide stakeholders (i.e., governments, entities, businesses and citizens), areas and infrastructures (e.g., buildings, homes, offices, urban parks, industrial plants) in order to offer sustainable services for people. The Internet of Things (IoT) paradigm helps the collection of a large amount of data that become available for decision makers and city managers, therefore impacting on all the three main aspects that characterise the concept of sustainability, together with the above mentioned urban metabolism: environmental, economic and social. Based on these considerations, in this paper we present and discuss the Arancino.cc(TM) system, mainly based on the use of open hardware and open software technologies in order to achieve 'green' benefits. These benefits essentially result in a better quality of life and a more efficient city management, and also optimise energy consumption and costs.
Keywords: urban metabolism; internet of things; smart city; sustainability; scientific data management.
A novel method for calculating the light energy distribution in building space
by Jundong Fu, Qing Chen
Abstract: In lighting design in buildings, the conventional algorithms may cause significant calculation error of light energy distribution and may not ensure illumination uniformity. In this paper, the radiation method in computer graphics is studied, combined with formula derivation, and two kinds of light energy calculation methods based on Lambert reflection model and non-Lambert reflection model are investigated. Two models, Model-1 and Model-2, are established for interior space of unequal height and non-rectangular interior space, respectively. Comparing simulation results of the models with existing models in a DIALux environment, the illumination uniformity calculation error of Model-1 is 30%, and the calculation error of Model-2 is within 5%. In addition, parameters of the models are modulated by experiments, in order to improve the accuracy of the models. Although Model-1 based on Lambert's reflection model runs fast, its accuracy needs to be improved. In the case of high simulation accuracy of spatial light environment, Model- 2 based on the non-Lambert reflection model is the best choice. At the same time, it is proved that the improved radiation method is feasible in calculating the light energy of an interior space with unequal height and non-rectangular shape.
Keywords: illumination calculation; light energy distribution; radiosity; Lambert reflection; non-Lambert reflection; global illumination.
Special Issue on: I3M 2018 Virtual and Augmented Reality in Industry and Logistics
Augmented Reality based solar system for e-magazine with 3-D audio effect
by Martin Sagayam Kulandairaj, Alex J. Timothy, Chung Ching Ho Peter, Lawrence Henesey, Robert Bestak
Abstract: Augmented reality (AR) is the newest technology that can be applied to computer vision, audio, video and other sensor-based input projects into 3D vision. It is the backbone for all specialisation of science, medical and engineering concepts. Currently, the reading and learning method through AR-based approach is quite highly intensive rather than the existing methods such as papers, books and magazines. This strategy is more expensive but it is more interactive to the user in understanding the root concepts in an effective manner. This paper additionally explores the experiment on solar system revolution pattern along with 3D audio effect in spatial dimension. This novel idea inculcates more vibrancy in the current generation of students to understand the concepts with clear illustrations and demonstrations.
Keywords: augmented reality; solar system; 3D vision; computer vision; 3D audio effect; 3D modelling.
Enabling outdoor MR capabilities for head-mounted displays: a case study
by Christoph Praschl, Oliver Krauss, Gerald Zwettler
Abstract: This research work covers generic approaches to determine the outdoor position and orientation of an augmented reality device due to the lack of outdoor capability of depth-sensor or environmental recognition-sensor based devices currently available on the market. The determination of the orientation is primarily achieved with an attitude heading reference system (AHRS) for a rough estimation. Based on a connected/built-in video camera the accuracy at minor changes of the orientation is enhanced by applying registration to assess the differences in orientation between two video frames, compensating gyroscope drift errors. The position determination is achieved using GPS with a rover and base station real time kinematic beacon system to achieve enhanced precision. Results show that owing to sensor application AR hardware considered for indoor use can be retooled to properly work outdoors, at large distances and even inside running vehicles. Thus, future implementation of applications in various domains is facilitated.
Keywords: augmented reality; orientation; positioning; image registration; modelling AR training scenarios.
Interactive design and architecture by using virtual reality, augmented reality, and 3D printing
by Samira Hosseini, Nora Aguilera, Hector Quintero, Fernando Suarez-Warden
Abstract: How do new methods of teaching architectural design consider the elements of religion, spirituality, modernism, history and other cultural factors to address the physical, spatial and emotional needs of society? The research presented in this study revolves around this question. This article presents a proposal for educational training that emphasises these elements for students of design and architecture. This paper describes a basic design course taught to second-semester students in the Design and Architecture program at Tecnologico de Monterrey on the Monterrey campus in Mexico. In the project, the professors planned the course to direct the basic concepts of design toward the inner sensations and feelings of a human being. To support this objective, the professors employed the digital technologies of virtual reality (VR), augmented reality (AR), and 3D printing. Digital technology has penetrated visual communication and subsequently caused profound changes in architectural design education. The new educational models incorporate the use of technologies that emphasise the human senses. The classrooms are being transformed into interactive spaces where the teacher uses strategies requiring the participants to work together to achieve the objectives of the course. Acquiring software to create two-dimensional (2D) and three-dimensional (3D) representations has become easier. However, it is essential to know the elements and principles of architectural design to create final products that meet the needs of the users. The technologies can be a means to achieve these ends. The results of this project demonstrated an increase in spatial visualisation, analysis, and critical thinking among the students. Additionally, 100% of the students showed high satisfaction with the course and the experience of using these technological tools in the Design and Architecture course.
Keywords: educational innovation; spatial visualisation; virtual reality; augmented reality; 3D printing; design process; cultural elements in architectural design.
Effectiveness of acoustic AR-TA agent using localised footsteps corresponding to audience members' attitudes
by Yuki Kitagishi, Tomoko Yonezawa
Abstract: We investigated an auditory augmented reality (AR) teaching assistant agent (AATA) that walks according to the participating attitudes of the audience members in one-to-many communications, such as lectures with over 100 audience members. If participants are not focused on the lecture, it is difficult to make them pay attention. To improve such audience members' attitudes or to draw the audience members' attention to the appropriate target, we propose an AATA expressed by moving the localised footsteps using a direction-controllable parametric speaker (DCPS). We conducted experiments based on the hypothesis that footsteps approaching an audience member indirectly would cause the audience member to notice his or her problematic attitude. According to the results, the participants felt as though someone, the teaching assistant (TA) or the lecturer, was walking around them when they perceived the movement of the localised footsteps, and they felt the changes in the AATA's attention and intention towards them when the AATA's walking pattern changed. Accordingly, it is proposed that the AATA's movement can deliver an implicit message, such as a warning, to the audience members.
Keywords: one-to-many communication; acoustic AR-TA agent; lecturer support; audience attention; ambient interaction; parametric speaker; presence of agent; localised sound.