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Colouring of COVID-19 Affected Region Based on Fuzzy Directed Graphs

computers, Materials & Continua 2021年第7期68卷 1219-1233页

作者： Rupkumar Mahapatra Sovan Samanta Madhumangal Pal Jeong-Gon Lee Shah Khalid Khan Usman Naseem Robin Singh Bhadoria Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar UniversityMidnapore721102India Department of Mathematics Tamralipta MahavidyalayaTamluk721636India Division of Applied Mathematics Wonkwang UniversityIksan-SiJeonbuk54538Korea School of Engineering RMIT UniversityMelbourne3001Australia School of Computer Science University of Sydney Sydney2006Australia Department of Computer Science&Engineering Birla Institute of Applied Sciences(BIAS)BhimtalUttarakhand263136India

Graph colouring is the system of assigning a colour to each vertex of a *** is done in such a way that adjacent vertices do not have equal *** is fundamental in graph *** is often used to solve real-world problems like traffic light signalling,map colouring,scheduling,***,social networks are prevalent systems in our ***,the users are considered as vertices,and their connections/interactions are taken as *** users follow other popular users’profiles in these networks,and some don’t,but those non-followers are connected directly to the popular *** means,along with traditional relationship(information flowing),there is another relation among *** depends on the domination of the relationship between the *** type of situation can be modelled as a directed fuzzy *** the colouring of fuzzy graph theory,edge membership plays a vital *** membership is a representation of flowing information between end nodes of the *** from the communication relationship,there may be some other factors like domination in *** influence of power is captured *** this article,the colouring of directed fuzzy graphs is defined based on the influence of *** with this,the chromatic number and strong chromatic number are provided,and related properties are *** application regarding COVID-19 infection is presented using the colouring of directed fuzzy graphs.

关键词： Graph colouring chromatic index directed fuzzy graphs

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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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Fuzzy Matrix Game A Fast Approach using Artificial Hybrid Neural-Net Logic-Gate Switching Circuit

Research Square

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Research Square 2022年

作者： Bhaumik, Ankan Roy, Sankar Kumar Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University West Bengal Midnapore721102 India

Introducing neuro-fuzzy concept in decision making problems, makes a new way in artificial intelligence and expert systems. Sometimes, neural networks are used to optimize certain performances. In general, knowledge acquisition becomes difficult when problem’s variables, constraints, environment, decision maker’s attitude and complex behaviour are encountered with. A sense of fuzziness prevails in these situations;sometimes numerically and sometimes linguistically. Neural networks (or neural nets) help to overcome this problem. Neural networks are explicitly and implicitly hyped to draw out fuzzy rules from numerical information and linguistic information. Logic-gate and switching circuit mobilize the fuzzy data in crisp environment and can be used in artificial neural network, also. Game theory has a tremendous scope in decision making;and consequently decision makers’ hesitant characters play an important role in it. In this paper, a game situation is clarified under artificial neural network through logic-gate switching circuit in hesitant fuzzy environment with a suitable example;and this concept can be applied in future for real-life situations. © 2022, CC BY.

关键词： Decision making

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A Generalization of σ-Permutability

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Communications in mathematics and Statistics 2022年第3期10卷 565-579页

作者： Zhigang Wang Jin Guo Inna N.Safonova Alexander N.Skiba School of Science Hainan UniversityHaikou 570228HainanPeople’s Republic of China Department of Applied Mathematics and Computer Science Belarusian State University220030 MinskBelarus Department of Mathematics and Technologies of Programming Francisk Skorina Gomel State University246019 GomelBelarus

Throughout this paper,all groups are finite and G always denotes a finite group;σis some partition of the set of all primes P.A group G is said to beσ-primary if G is aπ-group for someπ∈σ.Aπ-semiprojector of G[29]is a subgroup H of G such that HN/N is a maximalπ-subgroup of G/N for all normal subgroups N of ***П⊆σ.Then we say thatχ={X_(1),...,X_(t)}is aП-covering subgroup system for a subgroup H in G if all members of the setχareσ-primary subgroups of G and for eachπ∈Пwithπ∩π(H)≠φthere are an index i and aπ-semiprojector U of H such that U≤X_(i).We study the embedding properties of subgroups H of G under the hypothesis that G has aП-covering subgroup systemχsuch that H permutes with X^(x)for all X∈χand x∈*** well-known results are generalized.

关键词： Finite group σ-nilpotent group П-semiprojector П-covering subgroup system σ-subnormal subgroup

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An EOQ Model with Breakable Items Considering Stock Dependent Demand and Lead Time Dependent Credit Period

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International Journal of applied and Computational mathematics 2021年第6期7卷 1-26页

作者： Mallick, Rabin Kumar Patra, Kartik Mondal, Shyamal Kumar Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore 721 102 W.B. India Department of Mathematics Department of Mathematics Vivekananda Satavarshiki Mahavidyalaya Manikpara Paschim Medinipur 721513 W.B. India

In this paper, an EOQ model for breakable items to a retailer has been studied. Here, demand of the business is stock dependent. The breakability of the items is dependent on stock and holding cost. Here, a credit period has been offered to the retailer, which depends on lead time. Stock dependent demand and breakability are balanced by the lead time dependent credit period. The main intention of the present model is to detect the optimal order quantity, optimal lead time and to maximize the total profit of the whole business. To test our proposed model, two numerical examples are also illustrated. © 2021, The Author(s), under exclusive licence to Springer Nature India Private Limited.

关键词： Breakability Credit period Lead time Supply chain

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International Journal of applied and Computational mathematics 2021年第3期7卷 1-28页

作者： Sen, Sanjib Patra, Kartik Mondal, Shyamal Kumar Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore 721 102 W.B. India Department of Mathematics Vivekananda Satavarshiki Mahavidyalaya Manikpara 721 513 W.B. India

In this present work, a new similarity measure of Gaussian fuzzy numbers has been proposed. The proposed method is based on the exponent distance about mean, standard deviation and height of the Gaussian fuzzy numbers. The similarity has been measured in two different forms of Gaussian fuzzy numbers. Some properties corresponding to the proposed new method of similarity measure have been discussed. Also, the proposed method has been demonstrated with some examples of Gaussian fuzzy numbers. Finally, the proposed similarity measure has been applied in a job selection procedure considering the linguistic values of the Gaussian fuzzy numbers. © 2021, The Author(s), under exclusive licence to Springer Nature India Private Limited.

关键词： Asymmetric form Gaussian fuzzy numbers Job selection Linguistic terms Linguistic values Similarity measure Symmetric form

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Modeling of Memory Dependent Derivative Under Three-Phase Lag in Generalized Thermo-Viscoelasticity

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International Journal of applied and Computational mathematics 2021年第6期7卷 1-20页

作者： Singh, Biswajit Sarkar, Smita Pal Barman, Krishnendu Department of Mathematics Indian Institute of Engineering Science and Technology Shibpur Howrah 711103 West Bengal India Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Paschim Medinipur 721102 West Bengal India

In this study, a new generalized model of thermo-viscoelasticity with three phase-lag (TPL) theory concerning memory-dependent derivative (MDD) theory is emphasized. The governing combined equations of the novel model associated with kernel function and time delay are considered in a two-dimensional semi-infinite space. The bounding surface of the medium is assumed to be free of traction and subjected to time-dependent thermal loading. Using Laplace and Fourier Transform techniques, the problem is transformed from the space–time domain and then solved numerically. Suitable numerical technique is used to find the inversion of Fourier and Laplace transforms. In the simulation, the effects of the time-delay parameter and kernel function on the distributions of the displacement components, stresses and temperature field are studied and represented graphically. The results shows that the presence of TPL, the time-delay and kernel function extensively affect all the distributions. © 2021, The Author(s), under exclusive licence to Springer Nature India Private Limited.

关键词： Laplace and Fourier transform Memory dependent derivative Thermo-viscoelasticity Three phase-lag Vector matrix differential equation

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Multi-criteria Radio Frequency Identification Approach for Manufacturing Company Selection Based on Partitioned Maclaurin Symmetric Mean Operators Under Complex Intuitionistic Fuzzy Set Environment

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International Journal of Fuzzy Systems 2024年第5期26卷 1730-1748页

作者： Azam, Muhammad Jana, Chiranjibe Khan, Muhammad Sajjad Ali Pal, Madhumangal Xin, Qin Yang, Shilin Sarkar, Biswajit Faculty of Science Beijing University of Technology Beijing100022 China Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore721102 India Department of Mathematics Khushal Khan Khattak University Karak Khyber Pakhtunkhwa Karak27200 Pakistan Faculty of Science and Technology University of the Faroe Islands Tórshavn Faroe Islands Department of Industrial Engineering Yonsei University 50 Yonsei-ro Sinchon-dong Seodaemun-gu Seoul03722 Korea Republic of Center for Global Health Research Saveetha Medical College Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu 600077 Chennai India Department of Industrial Engineering and Management National Taipei University of Technology Taipei City 106344 Taiwan Chennai602105 India

The theory of intuitionistic fuzzy sets (IFSs) plays an essential role to deal with uncertainty and ambiguity. However, the IFSs deal only with anticipation, not periodicity. But, complex IFSs (CIFS) can handle both uncertainties and periodicity at a time. Therefore, this paper focuses on a new multi-criteria decision making (MCDM) approach using Maclaurin symmetric mean (MSM) operator in connection with the CIFS setting. Then, we develop some CIF partitioned based MSM (CIFPMSM) operators and their weighted form by considering that all the criteria can be arranged into some groups. The proposed operators not only deal with the interrelationship among criteria but also deal with the partitioned relationship among criteria. We discuss the properties of these proposed operators and investigate their cases. Finally, a decision-making approach for radio frequency identification (RFID) for manufacturing companies is developed based on the proposed operators and compared the results with the existing method to show the application and feasibility of the proposed method. © The Author(s) under exclusive licence to Taiwan Fuzzy Systems Association 2024.

关键词： Decision making

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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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The Modified Picture Fuzzy Weighted Geometric Operator for Decisionmaking Processes and its Applications to Ambient Air Pollution

SSRN

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SSRN 2023年

作者： Jaikumar, R.V. Raman, Sundareswaran Pal, Madhumangal Department of Mathematics St. Joseph’s Institute of Technology OMR Chennai India Department of Mathematics Sri Sivasubramaniya Nadar College of Engineering Chennai India Department of Applied Mathematics with Oceanology and Computer Programming Vidyasagar University Midnapore India

The aggregation operator is a popular tool for dealing with multi-criteria decision-making (MCDM) problems. An MCDM technique based on the modified picture fuzzy weighted geometric operator (MPFWGO) is proposed in this article. First, the drawbacks of various existing picture fuzzyweighted geometric aggregation operators (PFWGOs) that lead to imprecise outcomes in some exceptional instances are investigated. Second, an MPFWGO is proposed to address the shortcomings of existing PFWGOs. Furthermore, the suggested MPFWGO's properties such as idempotency, boundedness, monotonicity, and commutativity are explored. Numerical examples demonstrate that our proposed operator and corresponding MCDM approach are efficient and reasonable enough to prevent ambiguous results in exceptional instances. Finally, we applied the proposed method to rank the World Health Organization (WHO) regions for air pollution control. © 2023, The Authors. All rights reserved.

关键词： Decision making

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