Fuzzy Computing in Data Science: Applications and Challenges (Smart and Sustainable Intelligent Systems) - Hardcover

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Sachi Nandan Mohanty, PhD, received his doctorate from IIT Kharagpur in 2015 and his PostDoc from IIT Kanpur in 2019. He has recently joined as an associate professor at VIT-AP University, Andhra Pradesh. He has edited 24 books and published more than 100 research papers in international journals and has been elected as Fellow of the Institute of Engineers and Senior member of IEEE Computer Society Hyderabad chapter. His research areas include data mining, big data analysis, cognitive science, fuzzy decision-making, brain-computer interface, and computational intelligence.

Prasenjit Chatterjee, PhD, is an associate professor in the Mechanical Engineering Department at MCKV Institute of Engineering, India. He has more than 80 research papers in various international SCI journals. Dr. Chatterjee is one of the developers of a new multiple-criteria decision-making method called Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS).

Bui Thanh Hung, PhD, is the Director of Artificial Intelligence Laboratory, Faculty of Information Technology, Ton Duc Thang University, Vietnam, and received his doctorate from Japan Advanced Institute of Science and Technology (JAIST) in 2013. He has published numerous research articles in international journals and conferences as well as 14 book chapters. His main research interests are natural language processing, machine learning, machine translation, text processing, data analytics, computer vision, and artificial intelligence.

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This book comprehensively explains how to use various fuzzy-based models to solve real-time industrial challenges.

The book provides information about fundamental aspects of the field and explores the myriad applications of fuzzy logic techniques and methods. It presents basic conceptual considerations and case studies of applications of fuzzy computation. It covers the fundamental concepts and techniques for system modeling, information processing, intelligent system design, decision analysis, statistical analysis, pattern recognition, automated learning, system control, and identification. The book also discusses the combination of fuzzy computation techniques with other computational intelligence approaches such as neural and evolutionary computation.

Audience

Researchers and students in computer science, artificial intelligence, machine learning, big data analytics, and information and communication technology.