Hardcover. This book reflects the comprehensive exploration of the intersection between fuzzy decision-making and soft computing. It delves into the theoretical foundations of fuzzy decision-making and soft computing, exploring the underlying principles, algorithms, and mathematical frameworks. The text showcases the latest methodological advances in combining fuzzy decision-making with various soft computing techniques, such as neural networks, and evolutionary computation.This book:Provides a comprehensive coverage of data-driven decision-making techniques and soft computing methodsAim at bridging the gap between theoretical concepts and practical implementation by offering real-world case studies, examples, and applicationsHighlight emerging trends, recent advancements, and cutting-edge research in the field of data-driven decision-making and soft computingEmphasize the real-world relevance of Fuzzy Decision Making and Soft Computing by showcasing practical applications across various domainsShowcases applications in domains such as control systems, pattern recognition, optimization, and decision support systemsIt is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics, and communication engineering, computer science and engineering, and applied mathematics. This book reflects the comprehensive exploration of the intersection between fuzzy decision-making and soft computing. It delves into the theoretical foundations of fuzzy decision-making and soft computing, exploring the underlying principles, algorithms, and mathematical frameworks. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Bibliographic Details

Title: Data-driven Decision Making and Soft Computing (Hardcover)
Publisher: Taylor & Francis Ltd, London
Publication Date: 2026
Language: English
ISBN 10: 1041062974
ISBN 13: 9781041062974
Binding: Hardcover
Condition: new

About this title

Synopsis

This book reflects the comprehensive exploration of the intersection between fuzzy decision-making and soft computing. It delves into the theoretical foundations of fuzzy decision-making and soft computing, exploring the underlying principles, algorithms, and mathematical frameworks. The text showcases the latest methodological advances in combining fuzzy decision-making with various soft computing techniques, such as neural networks, and evolutionary computation.

This book:

Provides a comprehensive coverage of data-driven decision-making techniques and soft computing methods
Aim at bridging the gap between theoretical concepts and practical implementation by offering real-world case studies, examples, and applications
Highlight emerging trends, recent advancements, and cutting-edge research in the field of data-driven decision-making and soft computing
Emphasize the real-world relevance of Fuzzy Decision Making and Soft Computing by showcasing practical applications across various domains
Showcases applications in domains such as control systems, pattern recognition, optimization, and decision support systems

It is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics, and communication engineering, computer science and engineering, and applied mathematics.

About the Author

Nagarajan Deivanayagampillai received the PhD degree from Manonmaniam Sundaranar university. He is a highly accomplished professor in the Department of Mathematics at Rajalakshmi Institute of Technology and a Postdoctoral Researcher at the Faculty of Engineering and Technology, Multimedia University, Jalan Ayer Keroh Lama, 75450 Melaka, Malaysia. With 25 years of extensive teaching and research experience both nationally and internationally, he has made remarkable contributions to his field. He has published over 150 high-impact journal articles, secured four patent grants, and obtained one international copyright. He has successfully completed two international research projects and holds key editorial positions, serving as an Associate Editor for Franklin Open and an Academic Editor for the Journal of Mathematics, Advanced Fuzzy Systems, Computational and Mathematical Methods, and the International Journal of Biomedical Imaging. Additionally, he is a visiting professor for the Global Learning Programme (GLP) at ITS, Surabaya, Indonesia, and an esteemed editorial board member for several prestigious journals.

Dragan Pamucar received the M.Sc. degree from the Faculty of Transport and Traffic Engineering, Belgrade, Serbia, in 2009, and the PhD degree in applied mathematics, with a specialization in multi-criteria modeling and soft computing techniques from the University of Defence, Belgrade, in 2013. He is currently an Associate Professor with the Faculty of Organizational Sciences, University of Belgrade. He has five books and more than 220 research articles published in SCI-indexed international journals, including Expert Systems with Applications, Applied Soft Computing, Soft Computing, Computational Intelligence, Computers and Industrial Engineering, Engineering Applications of Artificial Intelligence, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions of Fuzzy Systems, IEEE Transactions on Transportation Electrification, Information Sciences, and Information Research. According to Scopus and Stanford University, he is among the World’s Top 2% of scientists as of 2020. According to WoS and Clarivate, he is among the Top 1% of highly cited researchers. His research interests include computational intelligence, multi-criteria decision-making problems, neurofuzzy systems, fuzzy, rough and intuitionistic fuzzy set theory, and neutrosophic theory, and their application areas include a wide range of logistics and engineering problems.

Zarife Zararsız received the M.Sc. and PhD degrees from Nevşehir Hacı Bektaş Veli University, Nevşehir, Turkey. She is an Associate Professor with Nevşehir Hacı Bektaş Veli University, Nevşehir, Turkey. Her research interests include sequence spaces, especially almost convergent sequence spaces and application of the fuzzy sets in medicine and other areas of the science.

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