Applications of Fuzzy Logic in Decision Making and Management Science
Idioma: inglés
Editorial: Palgrave Macmillan, 2026
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nach der Bestellung gedruckt Neuware - Printed after ordering - The fuzzy logic theory is a branch of mathematics dealing with uncertainty in measurement of any quantity or any estimation. The concept of fuzzy logic uses membership functions. The range of values from various functions or operations determines their construction. A defined rules set can create an application process and membership controls. Fuzzy applications include control system engineering, image processing, power engineering, industrial automation, robotics, consumer electronics and AI. Artificial intelligence, machine learning and expert systems have various applications that address complicated issues. The fuzzy logic inference rules have solved many problems in manufacturing and other industries. Auto engines by Honda, lift control by Mitsubishi Electric, palmtop computers by Hitachi, dishwashers by Matsushita and anti-lock brakes by Nissan are examples of corporations using machine-learning techniques with fuzzy principles. Fuzzy approaches and rule sets interpret computer vision, machine learning and evolution. Fuzzy sets can govern decision rules. Several areas use fuzzy systems in different ways. Computer vision, image processing and meta heuristic evolutionary computing are typical face research applications. Fuzzy theories can optimise and fine-tune the classifier model. Fuzzy theory is used in management, stock market analysis, information retrieval, linguistics, and behavioural science with good results. Fuzzy applications are seen in data mining and stock market prediction. The fuzzy machine learning model in the ensemble pattern accurately classifies and predicts all kinds of tasks. Fuzzy theories help maintain high accuracy. For categorisation and prediction, the ensemble pattern uses fuzzy concepts. The constant growth of fuzzy domain leads to several categorisation and prediction methods. Fuzzy type 2 and intuitionistic fuzzy logic exhibit promise accuracy and versatility. Such fuzzy logic variations can readily overcome the drawbacks of the simple fuzzy model.The book has been developed keeping in view about readers of different categories starting from the students to the professionals and researchers as well. The development of the book and its content layout will be done so meticulously proving the enough insights of the subjects to the readers so that the readers can easily pursue their research concept from the book. Overall the book serve as the purpose of repository of good amount of information and their technical presentations.…
N° de ref. del artículo 9783031777219
- Título
- Applications of Fuzzy Logic in Decision Making and Management Science
- Autor
- Biswadip Basu Mallik
- Editorial
- Palgrave Macmillan
- Año de publicación
- 2026
- Estado
- Neu
- Encuadernación
- Taschenbuch
- Idioma
- inglés
- ISBN 10
- 3031777212
- ISBN 13
- 9783031777219
- Peso del artículo
- 779 gramos
- Dimensiones
- 235x155x28 mm
The fuzzy logic theory is a branch of mathematics dealing with uncertainty in measurement of any quantity or any estimation. The concept of fuzzy logic uses membership functions. The range of values from various functions or operations determines their construction. A defined rules set can create an application process and membership controls. Fuzzy applications include control system engineering, image processing, power engineering, industrial automation, robotics, consumer electronics and AI. Artificial intelligence, machine learning and expert systems have various applications that address complicated issues. The fuzzy logic inference rules have solved many problems in manufacturing and other industries. Auto engines by Honda, lift control by Mitsubishi Electric, palmtop computers by Hitachi, dishwashers by Matsushita and anti-lock brakes by Nissan are examples of corporations using machine-learning techniques with fuzzy principles. Fuzzy approaches and rule sets interpret computer vision, machine learning and evolution. Fuzzy sets can govern decision rules. Several areas use fuzzy systems in different ways. Computer vision, image processing and meta heuristic evolutionary computing are typical face research applications. Fuzzy theories can optimise and fine-tune the classifier model. Fuzzy theory is used in management, stock market analysis, information retrieval, linguistics, and behavioural science with good results. Fuzzy applications are seen in data mining and stock market prediction. The fuzzy machine learning model in the ensemble pattern accurately classifies and predicts all kinds of tasks. Fuzzy theories help maintain high accuracy. For categorisation and prediction, the ensemble pattern uses fuzzy concepts. The constant growth of fuzzy domain leads to several categorisation and prediction methods. Fuzzy type 2 and intuitionistic fuzzy logic exhibit promise accuracy and versatility. Such fuzzy logic variations can readily overcome the drawbacks of the simple fuzzy model.
The book has been developed keeping in view about readers of different categories starting from the students to the professionals and researchers as well. The development of the book and its content layout will be done so meticulously proving the enough insights of the subjects to the readers so that the readers can easily pursue their research concept from the book. Overall the book serve as the purpose of repository of good amount of information and their technical presentations.
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Acerca del autor
Subrata Jana, double M.Sc. (Applied Mathematics, Applied Statistics and Analytics), M. Phil is an assistant professor of mathematics in the department of basic science and humanities at Seacom Engineering College, Howrah, West Bengal, India. Also he is working as a guest faculty of West Bengal State University, Barasat, West Bengal at the Department of Management and Marketing. Currently he is pursuing Ph.D. at Jadavpur University, Department of Mathematics. He has more than 10 years of Academic experience. His area of interest is Linear Algebra, Probability & Statistics, Operations Research, Mathematical Finance, Fuzzy Multi-Criteria Decision Making etc. He also acted as a resource person in various workshops and research programs conducted by Institutes. He has published several papers in national & international journals of repute. Also published a few papers in ABDC, Scopus, SCI, Web of Science and UGC Care listed journals and in edited books published by foreign publishers of repute like CRC Press, Routledge, Taylor & Francis etc. He is a life member of Calcutta Mathematical Society; Operational Research Society of India; Indian Statistical Institute, Kolkata; The Indian Science Congress Association.
Dr. Biswadip Basu Mallik is currently an Associate Professor of Mathematics in the Department of Basic Science & Humanities at the Institute of Engineering & Management, University of Engineering and Management, Kolkata, India. With over 22 years of experience in teaching and research, he has published numerous research papers and book chapters in scientific journals from esteemed international publishers such as CRC Press, Apple, Wiley, IGI Global, Springer, Nova Science, IEEE, and more. Dr. Basu Mallik has authored five undergraduate-level books on Engineering Mathematics, Quantitative Methods, and Computational Intelligence. He has also published five Indian patents and edited eighteen books. His research interests include Computational Fluid Dynamics, Mathematical Modeling, Optimization, and Machine Learning. He serves as the Series Editor for the book series titled Mathematics and Computer Science from Wiley-Scrivener, USA, and is the Managing Editor of the Journal of Mathematical Sciences & Computational Mathematics (JMSCM), USA. Additionally, Dr. Basu Mallik is an Editorial Board member and reviewer for several scientific journals. He holds senior life membership in the Operational Research Society of India (ORSI) and life membership in the Calcutta Mathematical Society (CMS), Indian Statistical Institute (ISI), Indian Science Congress Association (ISCA), and the International Association of Engineers (IAENG).
Dr. Anirban Sarkar is currently associated with West Bengal State University (WBSU) as Professor & Head of the Department of Management & Marketing. He is also the Director of Centre for Management Studies. He has more than 20 years of Academic experience. His area of interest is Marketing, Finance, and Statistics in Social Sciences particularly Market Research, Consumer Behaviour, Behavioural Marketing, Social Marketing, Digital Marketing, International Finance, and Behavioural Finance. He is now currently focusing on Data Analytics particularly Multivariate Analysis in Social Sciences. Completed minor and major research projects sponsored by UGC and ICSSR. Currently, submitted a Covid Special Project Report sponsored by ICSSR as Project Director. He chaired, co- chaired, and presented papers at many national and international conferences. He also acted as a resource person in various workshops and research programs conducted by Universities and Institutes of national importance across different states in India. Also published a few papers in ABDC, Scopus, SCI, Web of Science and UGC Care listed journals and in edited books published by foreign publishersofreputelikeRoutledge, Emerald, PalgraveMcMillan, Bloomsbury, etc. in the areas of general management, marketing, economics, and finance. Served as State Public Information Officer (SPIO) of WBSU from 2012 to 2016. At present also serving as Convener, Sports Board in WBSU since2016. He is a Life member of the Indian Economic Association (IEA), Bengal Economic Association (BEA), Indian Accounting Association (IAA), and Indian Commerce Association (ICA). Presently holding the position of Executive Council member and also Joint Secretary of the Indian Economic Association.
Dr. Chiranjibe Jana currently a adjunct faculty of Saveetha School of Engineering, Saveeth Institute of Medical and Technical Sciences (SIMATS), Chennai 602105, Tamil Nadu, India. He received his Bachelor of Science degree with honours in Mathematics in 2007 from Midnapore College, Paschim Medinipur, West Bengal, India and Master of Science degree in Mathematics in 2009 from Vidyasagar University, West Bengal, India. He received Ph.D degree in pure mathematics with specialization of fuzzy BCK/BCI- algebra and related algebras in 2018, Department of Applied Mathematics, Vidyasagar University, West Bengal, India. He has qualified NET in 2010. His current research interest are in the areas of multi-criteria decision-making, aggregation operator, decision- support systems, renewable energy, fuzzy optimization, artificial intelligence, fuzzy algebra and soft algebraic structures. He has published 84 papers, among them 50 are published in the international reputed SCI journals such as Applied Soft Computing, Engineering Applications of Artificial Intelligence, Scientia Iranica, International Journal of Intelligent Systems, Journal of Intelligent and Fuzzy Systems, Soft Computing, Journal of Ambinent Intelligence and Humanized Computing, Iranian Journal of Fuzzy Systems, Symmetry, Mathematics, and Knowledge-based Systems, Information Sciences, etc. He has published two edited books, one published in IGI Global, USA, 2019 and another published in Springer, 2023. He published one author book in Elsevier in November, 2023. He has serves as a reviewer in a journals including Soft computing, Artificial Intelligence Review, Journal of Ambinent Intelligence and Humanized Computing, Fuzzy Information and Engineering, Filomat, IEEE Access, International Journal of Intelligent Systems, Complexity, AIMS-Mathematics, Journal of Intelligent & Fuzzy Systems, The journal of Supper computing, Patter Recognition Letters, Engineering Applications of Artificial Inetlligence, Expert Systems with Applications, Applied Soft computing, and Information Sciences, etc. Now, he is an academic editor of Mathematical Problems in Engineering, SCIE, IF-1.305, and journal of mathematics, SCIE, IF-1.4, and He is a advisory board member of Heliyon journal, Elsevier, SCIE, IF-4. According to Scopus and Stanford University, he is among the World top 2% scientists as of 2022, 2023 and 2024.
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