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UPB Scientific Bulletin, Series C: Electrical Engineering and Computer Science 2016年第1 1期78 78卷 161-174页

作者： Baidya, Abhijit Bera, Uttam Kumar Maiti, Manoranjan Department of Mathematics National Institute of Technology Agartala-West-Tripura India Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University WB India

In this paper, we investigate six new transportation models with breakability and vehicle cost under some restriction on transported amount. An extra constraint on the total budget at each destination is imposed. Here six models are formulated under different environments such as crisp, stochastic and fuzzy. Using expected value of fuzzy number and chance constraint programming technique, we convert the respective fuzzy and random Models into its crisp equivalent. To get the preference of the objective function, we apply weighted sum method and a gradient based optimisation technique-generalised reduced gradient (GRG) method are applied and using LINGO-13 software to get the optimal solutions.

关键词： Stochastic systems

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Coordinating particle swarm optimization, ant colony optimization and k-opt algorithm for traveling salesman problem 3rd

Coordinating particle swarm optimization, ant colony optimiz...

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3rd International Conference on mathematics and Computing, ICMC 2017

作者： Khan, Indadul Maiti, Manas Kumar Maiti, Manoranjan Department of Computer Science Chandrakon Vidyasagar Mahavidyalaya Paschim-Medinipur West Bengal721201 India Department of Mathematics Mahishadal Raj College Mahishadal Purba-MedinipurWest Bengal721628 India Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Paschim-Medinipur West Bengal India

ISBN: (纸本)9789811046414

In this paper combining the features of swap sequence and swap operation based Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and K-Opt operation a hybrid algorithm is proposed to solve well known Traveling Salesman Problem (TSP). Interchange of two cities of a path of a TSP is known as swap operation and a sequence of such operations is called swap sequence. Using swap operation and swap sequence PSO operations are redefined to solve TSP. Here ACO is used a small number of iterations to generate initial swarm of PSO. Then PSO operations are made on this swarm a sufficient number of times to find optimal path. During PSO iterations if a particle does not change its position for a predefined number of iterations then K-Opt operation is made on it a finite number of times to improve its position. The algorithm is tested with bench mark test problems from TSPLIB and it is observed that algorithm is more efficient with respect to accuracy as well as execution time to solve standard TSPs (Symmetric as well as Asymmetric) compared to existing algorithms. Details of the proposed algorithm along with swap operation, swap sequence and K-opt operation for the algorithm are elaborately discussed for the readers. © Springer Nature Singapore Pte Ltd. 2017.

关键词： Ant colony optimization

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Connectivity index of m-polar fuzzy graph with application

Research Square

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Research Square 2021年

作者： Mandal, Sonia Pal, Madhumangal Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore 721102 India

This paper brings in connectivity index of a m-polar fuzzy graph (mPFG) with its boundedness. We investigate how the connectivity index of a mPFG changes when a vertex or an edge is deleted. Some special types of vertices include m-polar fuzzy connectivity enhancing node(mPFCEN), m-polar fuzzy connectivity neutral node (mPFCNN), m-polar fuzzy connectivity reducing node (mPFCRN) with their properties are discussed. © 2021, CC BY.

关键词： Fuzzy sets

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Application of Interval Type-2 Fuzzy Logic to polypropylene business policy in a petrochemical plant in India

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Journal of the Saudi Society of Agricultural Sciences 2018年第1期17卷 24-42页

作者： Jana, Dipak Kumar Castillo, Oscar Pramanik, Sutapa Maiti, Manoranjan Department of Engineering Science Haldia Institute of Technology Haldia Purba Midnapur 721 657 West Bengal India Tijuana Institute of Technology Tijuana Mexico Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore 721 102 West Bengal India

This paper presents a new approach to predict the quality of polypropylene in petrochemical plants. The proposed approach constructs four different models, based on a large number of data collected from a renowned petrochemical plant in India and uses it to predict the polypropylene quality. The quality of polypropylene depends on the indices such as melt flow index and the xylene solubility of the product and the parameters controlling these two indices are hydrogen flow, donor flow, pressure and temperature of polymerization reactors. Mamdani Interval Type-2 Fuzzy Logic inference systems are formed for first time. The model outcomes are compared with the collected plant data and a sequence of sensitivity analysis elects the most suitable model from them. Some sensitivity analyses are provided using Fuzzy C-Means Clustering to the models. © 2015 The Authors

关键词： Fuzzy C-Means Clustering Fuzzy inference system Interval Type-2 Fuzzy Logic Polypropylene Product quality

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An investigation on m-polar fuzzy saturation graph and its application

Research Square

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Research Square 2021年

作者： Mahapatra, Tanmoy Pal, Madhumangal Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore721102 India

The saturation graph is a well-defined topic. But, saturation in a fuzzy graph was defined recently and investigated many properties. In a fuzzy saturation graph, only one saturation is considered for every vertex. In a m-polar fuzzy graph (mPFG), each vertex and edge has a m number of membership values. So, defining saturation for mPFG is not easy and needs some new ideas. By considering m saturation for each component out of m components of membership values of a vertex, we defined saturation in mPFG. α-saturation as well as β-saturation in mPFG is introduced here. Many interesting properties of it are also presented. α-vertex count and β-vertex count in mPFG are also studied and the upper bound on some well known mPFG is also found here. Finally, a real-life application using saturation in mPFG is also presented. © 2021, CC BY.

关键词： Graph theory

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PREDICTION OF HEART DISEASE USING CLASSIFICATION AND FEATURE SELECTION METHODS 17

PREDICTION OF HEART DISEASE USING CLASSIFICATION AND FEATURE...

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17th International Symposium on Operational Research in Slovenia, SOR 2023

作者： Akarçay Pervin, Özlem Yapici Pehlivan, Nimet Weber, Gerhard Wilhelm KTO Karatay University Department of Computer Programming Konya Turkey Selçuk University Department of Statistics Konya Turkey Poznan University of Technology Poznan Poland Middle East Technical University Institute of Applied Mathematics Ankara Turkey

ISBN: (纸本)9789616165617

Heart disease, known as cardiovascular disease has been one of the main causes of death worldwide in recent years. It is affected by various risk factors such as high blood pressure, high cholesterol, diabetes, smoking, obesity, physical inactivity, etc. In this study, Cleveland database of UCI repository of heart disease patients is used. The dataset includes 303 instances and 76 variables which of 14 variables are considered. At first, three different feature selection techniques, namely LASSO, Elastic Net and Adaptive LASSO under specific tuning parameters determined by cross-validation, are applied to reduce the number of independent variables used for the prediction. Then, five different classification techniques, K-nearest neighbor, Support Vector Machine, Decision Tree, Random Forest, and Logistic Regression are performed to predict heart disease. Performances of these methods are measured by different metrics, such as accuracy, sensitivity, specificity, and Matthew correlation coefficient. © Proceedings of the 17th International Symposium on Operational Research in Slovenia, SOR 2023. All rights reserved.

关键词： Decision trees

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An EPQ Model of Deteriorating Items under Partial Trade Credit Financing and Demand Declining Market in Crisp and Fuzzy Environment

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Procedia Computer Science 2015年 45卷 780-789页

作者： P. Majumder U.K. Bera M. Maiti Department Of Mathematics National Institute of Technology Agartala Barjala Jirania pin:- 799055 Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore 721 102 India

In this manuscript, an Economic production quantity (EPQ) model have been formulated for deteriorating items under partial trade credit policy with crisp and fuzzy demand. For fuzzy demand we take demand as a triangular fuzzy number & we consider upper α 1 − cut & lower α 1 − cut of this fuzzy number. Then the annual inventory cost of retailer is divided into two parts upper α 1 − cut of annual inventory cost & lower α 1 − cut of annual inventory cost. We use weighted sum method to convert multi objective to a single objective. Here we have to derive optimum cycle time so as to minimize the total average cost. Numerical examples are used to illustrate all results obtained in this paper. Finally the model is solved by Generalized Reduced Gradient(GRG) method and using LINGO(12) software.

关键词： EPQ deterioration partial trade credit fuzzy demand.

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-Step fuzzy competition graphs

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Journal of applied mathematics and Computing 2014年第1期47卷 461-472页

作者： Samanta, Sovan Akram, Muhammad Pal, Madhumangal Department of Mathematics Joykrishnapur High School (H.S.) Tamluk India Department of mathematics University of the Punjab Lahore Pakistan Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore India

Presently, fuzzy graph theory has wide applications in engineering and social networks. Based on the applications, different types of fuzzy graphs are defined. Among them the competition graph is significantly used to model ecological problems. This graph is one kind of intersection graph. Different competitions of real world have been designed by fuzzy competition graphs. One generalization of fuzzy competition graph, called $$m$$ -step fuzzy competition graph, is defined in this paper. Some related fuzzy graphs including fuzzy $$m$$ -step neighbourhood graph, fuzzy economic competition graphs and fuzzy $$m$$ -step economic competition graphs are introduced. Some properties of these new graphs have been investigated.

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Analyzing the impact of machine learning and artificial intelligence and its effect on management of lung cancer detection in covid-19 pandemic

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Materials Today: Proceedings 2022年 56卷 2213-2216页

作者： Boddu, Raja Sarath Kumar Karmakar, Partha Bhaumik, Ankan Nassa, Vinay Kumar Vandana Bhattacharya, Sumanta Department of CSE Lenora College of Engineering Andhra Pradesh Rampachodavaram India Government of West Bengal Bikash Bhawan Salt Lake W.B. Kolkata India Dept. of Applied Mathematics With Oceanology and Computer Programming Vidyasagar University Midnapore India Department of Computer Science Engineering South Point Group of Institutions Sonepat Haryana India Department of Mathematics Dasmesh Khalsa College Zirakpur India Department of Science and Technology and Biotechnology MAKAUT India

Cancer victims, particularly those with lung cancer, are more susceptible and at higher danger of COVID-19 and associated consequences as a result of their compromised immune systems, which makes them particularly sensitive. Because of a variety of circumstances, cancer patients' diagnosis, treatment, and aftercare are very complicated and time-consuming during an epidemic. In such circumstances, advances in artificial intelligence (AI) and machine learning algorithms (ML) offer the capacity to boost cancer sufferer diagnosis, therapy, and care via the use of cutting technologies. For example, using clinical and imaging data combined with machine learning methods, the researchers may be able to distinguish among lung alterations induced by corona virus and those produced by immunotherapy and radiation. During this epidemic, artificial intelligence (AI) may be utilized to guarantee that the appropriate individuals are recruited in cancer clinical trials more quickly and effectively than in the past, which was done in a conventional and complicated manner. In order to better care for cancer patients and find novel and more effective therapies, It is critical that we move beyond traditional research methods and use artificial intelligence (AI) and machine learning to update our research (ML). Artificial intelligence (AI) and machine learning (ML) are being utilised to help with several aspects of the COVID-19 epidemic, such as epidemiology, molecular research and medication development, medical diagnosis and treatment, and socioeconomics. The use of artificial intelligence (AI) and machine learning (ML) in the diagnosis and treatment of COVID-19 patients is also being investigated. The combination of artificial intelligence and machine learning in COVID-19 may help to identify positive patients more quickly. In order to understand the dynamics of an epidemic that is relevant to artificial intelligence, when used in different patient groups, AI-based algorithms can quic

关键词： COVID-19

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Evolutionary Algorithm for Calculating the Optimal Temperature Regime of the Catalytic Process 5

Evolutionary Algorithm for Calculating the Optimal Temperatu...

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5th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2023

作者： Antipina, Evgenia Mustafina, Svetlana Antipin, Andrey Ufa University of Science and Technology Department of Scientific Research Ufa Russia Ufa University of Science and Technology Faculty of Mathematics and Information Technologies Ufa Russia Sterlitamak Branch of Ufa University of Science and Technology Department of Applied Informatics and Programming Sterlitamak Russia

ISBN: (纸本)9798350309126

The paper formulates an algorithm for searching the optimal temperature regime of the catalytic process in an ideal mixing reactor. The problem of optimal control of the catalytic process is formulated in a general form. To find its numerical solution, an algorithm based on the method of differential evolution is described. The algorithm allows to obtain an approximate solution of the optimization problem in a time acceptable from the practical point of view. A computational experiment for the dimerization process of alphamethylstyrene is carried out. The optimal temperature profile for achieving the maximum yield of reaction products - linear dimers - is obtained. © 2023 IEEE.

关键词： Evolutionary algorithms

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