International Journal of Artificial Intelligence and Soft Computing
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International Journal of Artificial Intelligence and Soft Computing (11 papers in press)
Fuzzy production-inventory models with shortages via ranking technique and credibility measure by Arindam Roy Abstract: In this paper, a production-inventory model for a defective / deteriorating item is developed with imprecise
inventory cost parameters. Here we have used two defuzzification techniques, (i) valuation/weighting function of Yager's ranking method, (ii) credibility measure, a compromise between optimistic and pessimistic measures for the deterministic transformation of the proposed model. A weighting function is added to Yager's ranking method so that it can represent the decision preference to solve a production inventory model. The proposed fuzzy inventory models are reduced to the crisp ones applying credibility measure. The problems are formulated as cost minimization problems and solved using a gradient-based non-linear programming technique. Finally, the models are illustrated through a numerical experiment with triangular fuzzy cost parameters. The results from two methods are compared and sensitivity analysis for different values of cost parameters and confidence levels (in credibility measure) is
presented. Keywords: Decision preferencernparameter; Weighting function; Credibility measure.
Deep Neural Networks For Multimodal Data Fusion And Affect Recognition. by Dhruv Bhandari, Sandeep Paul, Apurva Narayan Abstract: This paper proposes novel deep neural network models to handle multimodal data. The proposed models seamlessly facilitate fusion of multimodal inputs and bring about dimensional reduction of the input feature space. The architecture employs multimodal stacked autoencoder in conjunction with multi-layer perceptron based regression model. Two variants of the architecture are proposed. Experiments have been performed on the multimodal benchmark dataset (RECOLA) to illustrate the importance of multimodality for affect recognition. The proposed architectures are trained using effective training strategies, specifically designed to reduce the number of tuneable parameters for multimodal applications. The results obtained are encouraging and the proposed approach is computationally less expensive than the existing approaches. The performance is better or at par with the other techniques. Keywords: Multimodal Data; Stacked Autoencoder; Deep Neural Networks,rnData Fusion; Affect recognition; Emotional Recognition; Multimodal Stacked Autoencoder.
Scheduling Energy Storage Unit with GWO for Smart Home Integrated with Renewable Energy by Srivathsan Lakshminarayanan, Musbah Abdulgader, Devinder Kaur Abstract: The paper proposes a novel swarm based Grey Wolf Optimizer (GWO) algorithm to optimally schedule the Energy Storage Unit for a smart home integrated with the renewable energy resources such as wind and solar. The proposed method does not impose any restrictions regarding when to use appliances and ensures that all the household demands are met any time of the day. It reduces the cost of energy consumption for the user and at the same time balances the load on the grid by drawing less energy from the grid when the demand is high. Whenever the renewable energy resources are generating power, they are used for meeting the demand and to charge the ESU. The excess power generated is sold back to the utility at the same hourly price. The GWO was tested using data obtained from the United States Department of Energy for Chicago and outperformed PSO. Keywords: Smart Grid; Grey Wolf Optimizer; Swarm Intelligence; Green Energy; Natural Computing; Energy Storage.
Special Issue on: ICETMST 2018 Mathematical Modelling and Computation
Homomorphic Images and Shuffle Product on Probabilistic Automata by AROCKIA JEYAKUMAR J, Rajaretnam T Abstract: A probabilistic automaton (pa) is a fuzzy automaton, in which,sum of all fuzzy memberships of the initial states is one and from each state, on an input symbol, the sum of the fuzzy memberships of the transitions is one. In pa, it is shown that, if a morphism h is from a set to another set and inverse image of empty string maps to the empty string, then the image of a recognizable subset maps to a recognizable subset and if the maorphism h is fine, then the inverse image of recognizable subset is recognizable. It is also proved that the shuffle product of any two recognizable sets is recognizable. Keywords: probabilistic automaton; probabilistic behavior; fine morphism and shuffle product.
Diamond Tile Self-Assembly Shape Grammar System by M. Nithya Kalyani Abstract: A formal model of pseudo-crystalline self-assembly calledrnthe Tile Assembly Model, in which tile may be added to the growingrnobject when the total strength with its neighbours exceeds a parameterrnT . This model has been shown to be Turing-universal. Shape grammarrnderives designs in the language which it species by recursive applica-rntion of shape transformation rules to some starting shape. In this paper,rnDiamond tile self-assembly shape grammar system and Two-handed di-rnamond tile self-assembly shape grammar system have been introducedrnand investigated. Keywords: Self-assembly; Diamond tile self-assembly; Two-handedrnself-assembly; Shape grammar.
Structured Hexagonal Interactive System (SHIS) on PenneyS Coin Game by T. NANCY DORA, S.M. SAROJA T. Kalavathy Abstract: This paper gives an interesting probability game related to coin arrangements in structured hexagonal interactive system. Motivated by the study on Pennys Coin Game, Hexagonal Interactive System and Conway Algorithm, Structured Hexagonal Interactive System (SHIS) on PenneyS Coin Game have been constructed. SHIS scenario for computing the probability of winning player B is also presented. Keywords: Hexagonal Interactive System(HIS); Penny’s coin game;Conway Algorithm; Probability.
Equi-Triangular Array Grammars with Equal Matrix Type of Rules by Dharani Antony Cruz, Stella Maragatham Abstract: Generation of two-dimensional languages of picture arrays, rectangular, triangular, or hexagonal in shape, has been considered in several studies motivated by problems in picture processing and pattern recognition. Picture arrays in the form of equi-triangular arrays (et-arrays) composed of equilateral triangles and their generation by context-free type of array grammars have been considered recently. Here generation of picture languages of equi-triangular arrays based on equal matrix grammar type of rules is introduced and investigated. The rules in the matrix are regular type of rules except for initial rules. It has been proved that these equi-triangular array grammars with equal matrix grammar type of rules can generate picture languages of et-arrays that cannot be generated by context-free equi-triangular array grammars. Also the family of equi-triangular array grammars with equal matrix type of rule is shown to properly include the family of regular picture languages of et-arrays. Keywords: context-free grammar; equal matrix grammar; P system.
Segmenting ECG and MRI data using Ant Colony Optimization by B.S. Harish, C.K. Roopa, S.V. Aruna Kumar Abstract: This paper proposes efficient medical data segmentation using Ant Colony Optimization (ACO) and Modified Intuitionistic Fuzzy C-Means (MIFCM) clustering. MIFCM is a variant of Intuitionistic Fuzzy C-Means which uses modified Hausdorff distance measure to compute the distance between voxels and cluster centers. MIFCM handles uncertainty to a better extent compared to Fuzzy C-Means and its variants. However, MIFCM possesses the limitation that it initializes the cluster center randomly, which makes the algorithm converge to local optimal solution rather than global solution. Thus, ant colony optimization is proposed in this paper in order to overcome this. In this method, cluster centers are initialized based on ant colony optimization. To check the efficacy of the proposed method, the experiments are conducted on standard MRI brain tissue dataset and ECG arrhythmia dataset. The results of MRI brain tissue segmentation are evaluated in terms of Dice Coefficient (DC) and those of ECG arrhythmia segmentation are evaluated based on accuracy. Results are then compared with state-of-the art methods. Experimental results show that the proposed method performs better compared to other existing methods. Keywords: Segmentation; ECG; MRI; Intuitionistic Fuzzy C-Means; Ant Colony Optimization.
Special Issue on: ICETMST 2018 Mathematical Modelling and Computation
Inventory model with penalty cost and shortage cost using Fuzzy numbers by Rama Arun, G. Michael Rosario Abstract: In this paper an inventory model with penalty cost and shortage cost is formulated. The aim of this research work is to minimize the time period , total cost and the order quantity. To achieve this the formulated inventory model is converted to fuzzy inventory model by considering the parameters holding cost, demand and setup cost as pentagonal fuzzy number, triangular fuzzy number and trapezoidal fuzzy number. To find the optimum time period and optimum order quantity graded mean integration method and signed distance method is used for defuzzification. Numerical examples have been given in order to explain the model clearly .Sensitivity analysis is given for various values of deterioration time and also for comparing fuzzy numbers. Keywords: Fuzzy inventory model; shortage cost; penalty cost; defuzzification.
Context-Free Graph P System by Thanga Murugeshwari V, Emerald Princess Sheela J.D. Abstract: Graph grammar is a rewriting system generating graph languages. Context-free graph grammars are studied developing a theory similar to that of context-free string languages. In this paper we define context free node replacement graph P system with conditional communication and context free node replacement graph rewriting P system. Results on the notions such as the minimum number of membranes required to generate a family of context free graph languages are discussed. Keywords: Graph Grammars; Node replacement; P system.
Simulation of Universal Gates on P system using Catalysts by Barkavi R.S., Helen Chandra P. Abstract: A new generative model for simulation of universal gates on P system is proposed using catalysts. The simulation is done in P system with symbol objects, context free rewriting rules, features like mobile catalysts and weak priorities. The simulation of twin switch, Half Adder and Full Adder are also shown by means of an application. Keywords: P system,mobile catalysts and weak priorities.