Forthcoming and Online First Articles

International Journal of Simulation and Process Modelling

International Journal of Simulation and Process Modelling (IJSPM)

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International Journal of Simulation and Process Modelling (27 papers in press)

Regular Issues

  • Prediction of environmental factors in seafood cold chain transportation based on IAGA-ELM algorithm   Order a copy of this article
    by Yang Wang, Yujia Jin, Yinong Chen, Shenghui Zhao, Xu E 
    Abstract: Cold chain transportation is often used to ensure the quality of seafood. In order to reduce the impact of environmental factors on product quality during cold chain transportation, an environmental factor prediction method based on improved adaptive genetic algorithm (IAGA) and extreme learning machine (ELM) is developed to predict the environmental factors generated in cold chain transportation. The environmental factor data composed of the gases released in the decay mechanism of cold fresh seafood is collected for training ELM with fast training speed and strong generalisation ability. Furthermore, the prediction model of environmental factors in the process of seafood cold chain transportation is established. Because initial connection weights and threshold values of traditional ELM have the characteristics of randomness, IAGA is used to address this issue. Compared with the existing ELM, GA-ELM, AGA-ELM and other models, our experimental results show that the proposed model obtains higher prediction accuracy and lower error rate.
    Keywords: IAGA; ELM; cold chain transportation; environmental factors; prediction.

  • An integrated fuzzy AHP approach for optimisation of the theory of failures of multi-directional composite laminates   Order a copy of this article
    by Mohan Kumar Pradhan 
    Abstract: Owing to their improved engineering characteristics, composite materials have been widely used in various engineering fields over the past several decades. But unlike metals, composite materials failure is progressive and may be initiated in the form of breaking of fibres, micro-cracks in the matrix, etc., but its propagation and final failure modes may be considerably different.
    Keywords: analytic hierarchy process; theories of Failure; composite materials; fuzzy multiple criteria decision-making; synthetic evaluation.

  • Research on enterprise terminal network planning under the new retail format   Order a copy of this article
    by Siqi Zhang, Guanyang Li, Yiming Zheng, Yang Liu 
    Abstract: In view of the new retail online and offline omni-channel integration, with emphasis on customer consumption experience and delivery timeliness, this paper comprehensively considers customer satisfaction from two aspects of different levels of service costs and delivery timeliness, and establishes a bilevel programming model with the maximum comprehensive customer satisfaction and the lowest price of network planning. The paper uses AP clustering algorithm to cluster relevant customer areas, brings the clustering results into the model and applies the NSGA-II algorithm for further optimisation. Combined with the analysis of an example, the number, location, scale and service radiation range of the terminal network are planned reasonably, and the network model is innovated. The results show that the model and algorithm can effectively solve the problem of enterprise terminal network planning in the new retail format.
    Keywords: new retail; network planning; bilevel programming model; AP clustering algorithm; NSGA-II algorithm.

  • Risk analysis of road traffic accidents based on improved data mining method   Order a copy of this article
    by Tianjun Feng, Tan Gao 
    Abstract: According to the characteristics of road traffic accident data, two improved data mining methods are used to analyse the risk of accidents: nine accident-related factors are selected for discrete classification by weighted naive Bayes, the influence between factors is measured by weights and PMI thresholds, and the type of accident was predicted for a combination of factors. The accuracy of prediction increased from 83.98% to 87.02%. The traditional k-means algorithm is improved from three aspects: initial clustering centre, outlier point, and distance measurement. Through these improvements, the computational complexity of the clustering process is reduced and the clustering accuracy of accident-related factors is improved. On the one hand, the two methods can quantify the risk of accidents and facilitate the formulation of preventive measures; on the other hand, they can be used to improve the rationality of traffic safety evaluation.
    Keywords: road traffic accidents; data mining; analysis of the risk of accidents; weighted naive Bayes; improved k-means.

  • Simulation of heat transfer performance of silicone-based insulation coatings   Order a copy of this article
    by Li Wei, Kun Shen, Dongxu Wei, Kai Wang 
    Abstract: In order to investigate the heat transfer properties and insulation effect of silica-based insulation coating in pipe insulation, an ANSYS workbench is used, in this research work, to establish a thermal insulation model for heat transport pipes. The simulation study is carried out for silicon-based insulation coating, aerogel, aluminium silicate fibre, calcium silicate board, and other insulation materials with different thicknesses, different insulation structures, and different pipeline temperatures to compare their insulation effects, and the simulation results are verified with the tests that are carried out on the actual thermal pipelines, which show that silicon-based insulation coatings have a better thermal insulation effect than aluminium silicate fibre and calcium silicate board under the same boundary conditions and thickness, silicon-based insulation coatings have a better thermal insulation effect when the temperature is higher than 300
    Keywords: silicone-based eco-insulation coating; insulation structure; ANSYS workbench; numerical simulation.

  • A simulation study to evaluate the performance of FMS using routing flexibility   Order a copy of this article
    by Huzefa Mashhood, Mohammed Ali 
    Abstract: Flexible Manufacturing Systems (FMS) are used to withstand technological advancement in modern industries. Most studies have highlighted the difficulties in modelling FMS for analyses. The aim of this study is to develop a demonstrative model of FMS using ARENA and to study effects of routing flexibility on its performance. The conceptual, simulation model have been developed for various Routing Flexibility (RF) levels. Simulation results are used to find the optimum RF level. To validate the simulation results, grey relational analysis (GRA) and technique for order preference by similarity to ideal solution (TOPSIS) have been used. The study has shown that combination of RF1 level and inter-arrival time of 15 minutes results in optimized performance for the FMS. There are also the effects of dispatching rules on the performance of FMS. It is observed that both the rules do help in increasing the average system use and the system output.
    Keywords: flexible manufacturing systems; simulation; routing flexibility; GRA; TOPSIS.

  • Performance modelling and analysis of the assembly line system of leaf spring manufacturing plant using Petri nets   Order a copy of this article
    by Shanti Parkash, P.C. Tewari 
    Abstract: This work describes the performance modelling and analysis of the assembly line system of a leaf spring manufacturing plant. Availability is considered as a performance measure that is the function of reliability and maintainability of the plant. This work accents the use of the Reliability, Availability, Maintainability and Safety (RAMS) tool, which can reduce the uncertainties of the plant availability using certain software. It covers all stages of the product development process. Simulation and modelling among four subsystems in various conditions is done by a Petri module of GRIF software. This work investigates effect of various repair and failure rates of different subsystems on the performance of a system in terms of availability. Decision Support System (DSS) has been proposed for this system. The outcomes of this paper might be helpful for the maintenance department to provide futuristic priorities for the critical subsystem, which can helpful to increase the system performance.
    Keywords: reliability; availability; maintainability; safety; decision support system; Petri nets.

  • Agent-based simulation of pedestrian movement: a gradient method with an amplification parameter   Order a copy of this article
    by Michal Dziecielski, Marcin Wozniak 
    Abstract: Pedestrian transportation is becoming increasingly important in modern cities. In this paper, we develop an agent-based model to simulate pedestrian traffic in a city. The real residential area represented by geographic information system (GIS) data was used. This paper aims to show the general model of pedestrian movements that can be applied to both small neighbourhood spaces and whole districts. It can be also used to simulate pedestrian traffic in open as well as closed spaces. A gradient method with an additional parameter related to the distance between the agent and the target was used. What was visualized in the first step were the trajectories of agents movement and analysed lengths of routes, as well as the time needed to reach the destination by agents. The second step involved sensitivity analysis. Morris screening results show that the impact of all parameters is significant and highly diversified. Non-linear dependencies between model inputs were detected. The article also shows different walking strategies, e.g. leisure walk or rush to the target. Simulations present how agents move to their destination navigating and avoiding obstacles they face.
    Keywords: agent-based modelling and simulation; pedestrian modelling; geographic information system; sensitivity analysis; Morris screening.

  • Predictive modelling of pump noise using multi-linear regression and random forest models, via optimal data splitting   Order a copy of this article
    by Mir Mohsin John, Suhail Ganiny, Mohammad Hanief 
    Abstract: In this paper, the multi-linear regression and random forest method are used to model and predict the noise produced in an axial piston pump. Experimental data pertaining to 120 trials is used to model and predict the pump noise as a function of valve seat material (characterized by material density), pump speed and pressure. The models are developed using an optimum data proportion, determined using K-fold cross-validation technique, of available experimental data allocated for model training and model testing. The most dominant factor affecting the noise is identified using the developed models along with the analysis of variance technique. For comparison purposes, a cascaded neural network with two hidden layers is also used for modelling and predicting the pump noise. The results of our analysis reveal that the random forest method is statistically better than the multi-linear regression and cascaded neural network models in modelling and predicting the noise generated by axial piston pumps. In particular, the mean-squared error (MSE) between the three regression models and the cascaded neural network model with respect to the experimental data are 10.82, 4.95 and 3.97, and 1.26, and the values of the coefficient of determination (R2) are 0.79, 0.92, 0.93 and 0.96, respectively. The corresponding values for the predictions made by the random forest model are 0.56 and 0.98 which clearly indicate the statistical significance of the random forest model as compared to the linear regression and cascaded neural network models. Moreover, pump speed is found to be most dominant factor affecting the noise emission while the valve seat material turns out to be the least dominant.
    Keywords: axial piston pumps; pump noise; prediction; regression; random forest; artificial neural network; K-fold cross-validation.

  • Sensorless control of direct-driven PMSG wind turbines using NPIC and MRAS observer   Order a copy of this article
    by Ahmed Elgharib, Soufyane Benzaouia, Aziz Naamane 
    Abstract: This article presents a sensorless control technique of a direct driven permanent magnet synchronous generator wind turbine. The proposed sensorless approach uses an MRAS observer to estimate the generator rotational speed. This latter needs only three phase voltage and current measurements provided by the cheapest electrical sensors. There are two main objectives in this article: First one is extracting and achieving the maximum power point using a vector control technique based on nonlinear proportional integral controller, while the second one is avoiding the use of mechanical speed sensor by using the MRAS observer for cheaper implementation. Such an article shows the performance of the whole system by using the proposed control strategy with and without a speed sensor. The obtained results prove the efficiency and effectiveness of the developed approach.
    Keywords: wind turbine modelling and simulation; permanent magnet synchronous generator; wind turbine standalone system; non-linear proportional integral controller; maximum power point tracking; model reference adaptive system.

  • Operations planning in outpatient chemotherapy with hybrid simulation modelling   Order a copy of this article
    by Mahmoud Heshmat, Amr Eltawil, Mohammed Abdelghany 
    Abstract: An Outpatient Chemotherapy Clinic (OCC) is a crucial medical unit where cancer is diagnosed, and treatments are provided. However, it faces planning and scheduling challenges. In this paper, two problems in OCCs are addressed: how to accurately compute the utilisation of the nurses, and the patient appointment scheduling problem. An agent-based simulation is used to simulate the nurse activities and thus the nurse utilisation is computed. A discrete event simulation model is developed to evaluate the performance of the current patient appointment practice. However, the resulted nurse utilisation could not be accurately computed. Therefore, a hybrid discrete event and agent-based simulation model is developed to simulate the whole system, including the nurse activities. Moreover, the proposed simulation model is used to determine the best scenario for patients' appointments. These results can be used to accurately compute the nurse utilisation in the OCCs beside the other key performance indicators in OCCs.
    Keywords: simulation; outpatient chemotherapy; discrete event simulation; agent-based simulation; patient appointment scheduling.

  • Modal behaviour of spur gear pairs for a low speed transmission application: a comparative study between symmetric and asymmetric gears   Order a copy of this article
    by Krishanu Gupta, Sushovan Chatterjee 
    Abstract: Modal analyses on the types of involute profile spur gear is investigated in this work using the FEM analysis platform considering the no-load condition. The gear pairs resonance frequency behaviours were mapped against the first six mode shapes. A comparison study has also been carried out for the involved types of gear pairs, making it prominent, between symmetric and asymmetric gear pairs. From this analysis, it was noticed that the asymmetric gear pair bears a high range of resonating frequencies in comparison to other symmetric involute gear teeth pairs. Attempts had been made to examine specific range of higher values of frequencies for asymmetric gear pair than any other asymmetric pairs at different modes by modal analysis.
    Keywords: spur gear; symmetric and asymmetric gear pair; natural frequency; mode shape; deformation.

  • Strategic digital shipbuilding project portfolio configuration and optimisation   Order a copy of this article
    by Rafael Diaz 
    Abstract: Program portfolio managers in digital transformation projects need knowledge that can guide allocation decisions associated with the configuration of project assets within the sustainable and strategic objectives of the firm. This research aims to propose a framework capable of optimising the cost-benefit adjustments from assessing investment risks of digital transformation projects such as cybersecurity projects. The context considers the innovative sector of military shipbuilding and repair. Our approach uses an artificial neural network (ANN) and Monte Carlo simulation modelling to capture risk effects and quantify investment priorities. This method enables the application of portfolio management theory principles to measure and optimise the performance of the digitalisation project portfolio. The framework's utility is discussed using a hypothetical case study presenting several digital transformation project investment scenarios.
    Keywords: project management; portfolio management; neural networks; cost analysis; training.
    DOI: 10.1504/IJSPM.2022.10051161
  • The modelling of balance between energy efficiency and economy and simulation analysis in electric gas production technology   Order a copy of this article
    by Jiajun Wang, Yahui Wang, Wenjie Qi 
    Abstract: The simulation optimisation analysis on electric gas production technology (power to gas, P2G) was conducted by exergy analysis method. The energy efficiency equation of electrolysis water and methanation in P2G was established. The net present value (NPV) method was used to analyse the economy of P2G and the economy equation of P2G is established. The balance between economy and energy efficiency of the system was adjusted using the optimisation weight coefficient. The optimisation model of balance between energy efficiency and economy in P2G and its constraint equation are established, and the optimisation simulation analysis was carried out by combining Lagrange relaxation and branch-and-bound method. The analysis results have shown that the profit of the P2G is affected by the efficiency of electrolysis water and methanation as well as equipment investment. By optimising the P2G process and investing the equipment reasonably, the maximum economic benefit of the P2G system can be obtained.
    Keywords: electric gas production technology; exergy; energy efficiency; economy; simulation analysis.
    DOI: 10.1504/IJSPM.2022.10051154
  • Using discrete event simulation to optimise cementing resources: a case study analysis using a call-out strategy for onshore rigs   Order a copy of this article
    by Maclean Iral Dsouza, Mohamed K. Watfa 
    Abstract: A standard resource configuration is to allocate one cementing package for each rig, which does not utilise the capital-intensive cement unit resource optimally. The objectives of this study are to study the economic implications of the proposed call-out strategy, an implementation of the just-in-time philosophy and develop a discrete event simulation (DES) model improve operations' efficiency. To demonstrate the practicality of our model, three case studies with real collected data over a period of five years for a leading oil and gas company in the Gulf area were considered and the relationship between the optimal number of cementing units and the number of rigs was rigorously analysed: optimal number of cement units = 1.489 + 0.525 (number of rigs). Results indicate that optimisation of the cementing units and human resources can be achieved with effective resource reallocation to different rig configurations while considering realistic factors of capacity planning, efficiency utilisation and delivery of cementing services without non-productive time.
    Keywords: call-out strategy; cementing unit resources; operations research; drilling rigs; arena; optimisation; discrete event simulation; DES.
    DOI: 10.1504/IJSPM.2022.10051159

Special Issue on: I3M2020/ISM2020 Smart Interaction for the 4.0 Domains Modelling and Simulating the Content of the Future

  • A simulation study on how to optimally store products in a warehouse of a fashion supply chain selling through an e-commerce channel   Order a copy of this article
    by Eleonora Bottani, Letizia Tebaldi, Mariachiara Rossi, Giorgia Casella 
    Abstract: Where is it convenient the most to allocate a determined product? This paper, by means of a simulation tool, makes an attempt to answer this question, for the specific case of an e-commerce warehouse in which fashion items are stored. According to the typical steps of the Deming cycle, after having studied the current situation (AS IS scenario) of items allocation, a simulated one (TO BE scenario) was developed for studying a new allocation strategy, and for its assessment four key performance indicators were considered: the storage and picking productivity (both expressed in terms of processed units per hour), the % of FIFO batch for multi-customer orders and the time spent for batching (measured in hours). Results from the implementation show an improvement of the KPIs under investigation, as well as the observation of the specific targets set, and consequently an optimisation of picking activities.
    Keywords: warehouse optimisation; picking optimisation; PDCA; product allocation optimisation; logistics; e-commerce; fashion supply chain; simulation; case study.
    DOI: 10.1504/IJSPM.2022.10047459
  • An information-based model to assess human cognitive capacity and information processing speed of operators in Industry 4.0   Order a copy of this article
    by Daniela Cavallo, Salvatore Digiesi, Francesco Facchini, Giovanni Mummolo 
    Abstract: The fourth industrial revolution introduced a new paradigm in manufacturing systems. In the new production environments, operators are supported by new digital technologies, and the physical context is strictly related to the cyber one. In the digital society, recent studies show that individuals have to perform tasks based on the information gathered by a huge amount of data and the operators are employed in more cognitive than physical tasks. Therefore, the purpose of this paper consists in developing an information-based analytical framework to assess the human cognitive capacity occupancy and the human processing time of correct information when the quality performance is known. The model has been tested on case studies. The results show its effectiveness in evaluating the human mental workload imposed by the task performed and the processing speed of correct information with varying quality performance.
    Keywords: cognitive task; mental workload; MWL; HIPS; smart operator; information theory model.
    DOI: 10.1504/IJSPM.2022.10051157
  • A numerical assessment of the influence of Industry 4.0 technologies on the cognitive complexity of procedure-guided tasks   Order a copy of this article
    by Andrea Lucchese, Francesco Facchini, Giorgio Mossa, Giovanni Mummolo, Francesco Paolo Sisto 
    Abstract: In Industry 4.0 (I4.0) context, procedure-guided tasks are characterised by a greater complexity due to the higher cognitive nature. On one side, increasing information processing demand and more articulated decision-making processes are required in new factories. On the other side, different I4.0 technologies are available to support workers in work environments. In this regard, the entropy measures were adopted to evaluate how the cognitive complexity required by general procedure-guided tasks changes when the I4.0 technologies are implemented. Results show that the implementation of I4.0 technologies decreases the information processing demand of the task (estimated in bit/s), reducing the cognitive effort of operators. Furthermore, the numerical simulation shows that adopting I4.0 technologies, an operator is able to perform a task 20% more complex (estimated in bit). Consequently, the study conducted allowed to predict how the information processing demand of procedure-guided tasks can be affected by implementing I4.0 technologies.
    Keywords: cognitive complexity; task complexity; procedure-guided tasks; I4.0 technologies; Industry 4.0; entropy measure; task structure.
    DOI: 10.1504/IJSPM.2022.10051158
  • Digital clones and digital immunity: adversarial training handles both   Order a copy of this article
    by Vladyslav Branytskyi, Mariia Golovianko, Svitlana Gryshko, Diana Malyk, Vagan Terziyan, Tuure Tuunanen 
    Abstract: Smart manufacturing needs digital clones of physical objects (digital twins) and human decision-makers (cognitive clones). The latter requires use of machine learning to capture hidden personalised decision models from humans. Machine learning nowadays is a subject of various adversarial attacks (poisoning, evasion, etc.). Responsible use of machine learning requires digital immunity (the capability of smart systems to operate robustly in adversarial conditions). Both problems (clones and immunity training) have the same backbone solution, which is adversarial training (learning on automatically generated adversarial samples). In this study, we design and experimentally test special algorithms for adversarial samples generation to fit simultaneously both purposes: to better personalise decision models for digital clones and to train digital immunity, thus, ensuring robustness of autonomous decision models. We demonstrate that our algorithms facilitate the desired robustness and accuracy of the training process.
    Keywords: digital cloning; digital immunity; Industry 4.0; adversarial machine learning; adversarial example generation; machine learning; generative adversarial networks; process modelling.
    DOI: 10.1504/IJSPM.2022.10048910

Special Issue on: ISSPM2020 Advances in Simulation and Process Modelling

  • A methodology to characterise simulation models for discovery and composition: a system theory based approach to model curation for integration and reuse   Order a copy of this article
    by Bernard Zeigler 
    Abstract: We make a strong assumption that we can extract the necessary and sufficient information needed to decide whether a simulation model is suitable for an analyst's problem and that it contains information on how to be configured, integrated, and executed. This assumption allows us review an approach that is founded on the theory of modelling and simulation and employs tools to develop, simulate, and apply models expressed in the Discrete Event System Specification (DEVS) formalism, a sound systems theory-based computational methodology for system-of-systems model development and deployment. This foundation allows us to discuss how to apply the well-developed theory to curate simulation models so that they can more easily be discovered from a model repository given analytical objectives. After outlining the methodology, we place it in a broader context in which web- and cloud-based technologies are employed for integration and to enable modelling and simulation as a service. Significant technical challenges are described that require continued research and development.
    Keywords: DEVS; theory of modelling and simulation; model curation; reusability; composability.

  • Simulation of pork supply chain based on system dynamics model   Order a copy of this article
    by Qianqian Shao, Xiaojing Zhang, Chong Li, Yang Liu 
    Abstract: In most of the advanced researches of pork supply chain (PSC) analysis, the systematic behaviour is only studied locally, and does not focus on the influence of different consumer demand changes on the system behaviour. In order to make the simulated PSC more authentic, different combinations of three demand types (random demand, sudden demand and cyclical demand) are considered in this model. Within the PSC, there is a causal relationship between the actions of enterprises. System dynamics (SD) can build complex system models to solve complex dynamic problems. Therefore, we analyse the PSC and integrate the system flow diagram and variable equations into a SD flowchart to study the internal behaviour. Taking Shenyang (China) PSC in 2020 as an example, the system behaviour was observed. In addition, the influence of price delay and transportation delay on pork price is further discussed.
    Keywords: pork supply chain; system dynamic; pork price; flow diagram.

  • Simulation optimisation of displaced left-turn intersection layout with multi-objectives   Order a copy of this article
    by Qianqian Shao, Yingcheng Zheng, Yang Liu, Yan Xing 
    Abstract: The displaced left-turn (DLT) intersection, which effectively solve the conflict between left-turn and opposing-through traffic, is currently the most efficient innovative intersection design. However, the special layout of DLT will inevitably cause high difficulty in channelisation design. For full use of the potential traffic capacity of the DLT intersection, a multi-objective optimisation model for intersection with DLT layout (MOOM-DLTL) is built based on the integrated simulation and mathematical programming (ISMP) framework. In this model, the signal scheme is regarded as the accompanying strategy of DLT layout optimisation to describe the interaction between layout and signal control. In addition, the multi-objective particle swarm optimisation based on shift-based density estimation (MOPSO+SDE) algorithm is developed to obtain the Pareto front of the proposed model. A series of experimental results show that the proposed optimisation method is successful in improving the traffic efficiency of DLT intersection.
    Keywords: displaced left-turn; multi-objective optimisation; layout design; MOPSO.

  • Effect of cap gap and welded seam strength on concrete-filled steel tube arch bridge ribs   Order a copy of this article
    by Zhengran Lu, Chao Guo 
    Abstract: In this paper, the quantitative analysis is investigated for the concrete-filled steel tube rib strength that contained defects. The friction Coulomb model was used to investigate the interaction between the steel tube and the concrete core. Based on the non-destructive testing data, the finite element analysis is simulated with ABAQUS to obtain the strength of serviced concrete-filled steel tube ribs containing cap gaps and reduced spiral-welded seam strength which are exposed to weak eccentric axial compression. The results show that spiral-welded seam defects have weaker influence on the bearing capacity of CFST than that on empty steel tube. However, it has a significant influence on CFST local yield failure mode. The cap gap defects have effect on the shape of N-? relationships. For CFSTs with composite defects, welded seam defects weakened local steel tube restrain capacity to concrete, resulting in CFST bending failure.
    Keywords: composite defect; finite element method; concrete-filled steel tube; spiral welded seam; cap gap.

  • Research on travel time prediction of expressway in peak period based on Greenberg model   Order a copy of this article
    by Yan Xing, Yuqing Hao 
    Abstract: Expressway travel time is an important parameter to describe the traffic status of the expressway, which can accurately evaluate the smoothness of the expressway and can reflect the efficiency of expressway traffic. To further improve the research content of expressway travel time prediction, simplify the complexity of the travel time prediction method, and improve the prediction accuracy, in this paper, the travel time prediction of the expressway is divided into three cases: exit between two cross-sections, entrance between two cross-sections, and no entrance/exit between two cross-sections. First of all, based on the Greenberg model, assuming a uniform distribution of vehicles on the road section, and under the premise of a comprehensive analysis of the section flow, section traffic density, and other factors, respectively, to establish different sections under the peak period expressway vehicle travel time prediction model. Finally, the model is verified by taking the expressway around the city as an example. The results show that the prediction results are always within 10% of the actual measurement error, which shows that compared with the measured data, the error of the model proposed in this paper is small, the prediction accuracy is high, within the acceptable range. The calculation is relatively simple, and has good application value and comprehensive performance.
    Keywords: travel time prediction; entrance/exit ramp; Greenberg model; peak expressway.

  • Research on fire escape paths for complex public buildings with multiple starting and end points   Order a copy of this article
    by Yi Zhang, Chi Wang, Wenwen Tong, Tianqi Liu 
    Abstract: In order to solve the path-planning problem in the escape and evacuation of dense crowds in complex buildings, an improved Dijkstra's algorithm is proposed in this paper to carry out a research on the planning of the shortest escape path from the starting point of the crowds to the security exit of the building. In order to test the effect of the algorithm, the simulation of the proposed improved algorithm has been carried out in the paper using real commercial bodies as a model with different number of people and different distribution densities. The experimental results verify that the proposed algorithm is fast and efficient and can effectively improve the escape efficiency of the crowds, which has strong application value.
    Keywords: improved Dijkstra's algorithm; multiple starting and end points; evacuation; path planning;.

  • A novel analytical model for estimating vehicle delays at isolated signalised intersections   Order a copy of this article
    by Feng Qiao, Huixin Liu, Dan Luo, Haochen Sun, Yinong Chen 
    Abstract: This paper proposes a novel analytical model to estimate the average vehicle delay at signalised intersections under saturated or oversaturated conditions, based on the investigation and analysis of the existing methods to deal with the problems arising in the processes of acceleration, deceleration, and the transmissibility of the cycle-by-cycle average vehicle delay. The proposed model employs and combines the operating and queuing characteristics of vehicles to produce the analytic formula. To verify the effectiveness of the proposed model, simulation experiments are conducted, and the error rates and the correlation coefficients are investigated, which confirm that the proposed model possesses certain significant advantages over the existing models in saturated and oversaturated conditions. The results of research work show that the proposed model can provide transportation engineers or professionals with an effective tool for analysing, timing and managing the saturated or oversaturated signalised intersections.
    Keywords: signalised intersection; analytical model; vehicle delay; saturated condition; oversaturated condition; operating characteristics.

  • ARIMA based time-series analysis for forecasting of Covid-19 cases in Egypt   Order a copy of this article
    by Ibrahim Sabry, Abdel-Hamid Ismail Mourad, Amir Hussain Idrisi, Mohamed El-Wakil 
    Abstract: This novel coronavirus is one of the world's most devastating viruses at the moment and currently constitutes a major threat to human health. Globally, approx. three hundred million people have been infected, resulting in the deaths of more than five million people. The goal of this study is to understand the distribution of Covid-19 in Egypt. A mathematical model was developed using data collected from the Egyptian Ministry of Health. A major purpose of this study is to examine the distribution of Covid-19 in Egypt in order to develop an effective forecasting model. It can be used as a decision-making mechanism to administer health interventions and mitigate the transmission of contamination Covid-19. In accordance with this definition, we developed a model and then used it to predict possible Covid-19 cases in Egypt. The analysis suggests a growth trajectory for the events in the days to come. Statistics based on time series analysis and kinetic model analysis suggest that the total cases of Covid-19 pneumonia in mainland Egypt can hit 281478 after a week (1 March, 2020 through July 31, 2021), and the number of simple regenerations can hit 12. Analysis of ARIMA (2, 1, 2) and (2, 1, 3) sequence shows increasing growth in the number of events. The current model forecasts would help the government and medical personnel to plan themselves for the coming conditions and make healthcare systems more ready.
    Keywords: coronavirus; Covid-19; pandemic; ARIMA; forecast; Egypt.