Overview
Decision Making Models: A Perspective of Fuzzy Logic and Machine Learning presents the latest developments in the field of uncertain mathematics and decision science. The book aims to deliver a systematic exposure to soft computing techniques in fuzzy mathematics as well as artificial intelligence in the context of real-life problems and is designed to address recent techniques to solving uncertain problems encountered specifically in decision sciences. Researchers, professors, software engineers, and graduate students working in the fields of applied mathematics, software engineering, and artificial intelligence will find this book useful to acquire a solid foundation in fuzzy logic and fuzzy systems. Other areas of note include optimization problems and artificial intelligence practices, as well as how to analyze IoT solutions with applications and develop decision-making mechanisms realized under uncertainty.
Full Product Details
Author: Tofigh Allahviranloo, PhD (Full Professor, Istinye University, Istanbul, Turkey) ,
Witold Pedrycz, Ph.D. (Professor, Department of Electrical and Computer Engineering, University of Alberta, Canada) ,
Amir Seyyedabbasi (Assistant Professor, Istinye University, Istanbul, Turkey)
Publisher: Elsevier Science Publishing Co Inc
Imprint: Academic Press Inc
Weight: 0.450kg
ISBN: 9780443161476
ISBN 10: 044316147
Pages: 678
Publication Date: 25 July 2024
Audience:
Professional and scholarly
,
College/higher education
,
Professional & Vocational
,
Postgraduate, Research & Scholarly
Format: Paperback
Publisher's Status: Active
Availability: Manufactured on demand
We will order this item for you from a manufactured on demand supplier.
Author Information
Tofigh Allahviranloo is a full professor of applied mathematics at Istinye University, Turkey. As a trained mathematician and computer scientist, Prof. Allahviranloo has developed a passion for multi- and interdisciplinary research. He is not only deeply involved in fundamental research in fuzzy applied mathematics, especially fuzzy differential equations, but he also aims at innovative applications in the applied biological sciences. He is the author of several books and many papers published by Elsevier and Springer. He actively serves the research community, as Editor-in-Chief of the International J. of Industrial Mathematics, and Associate Editor or editorial board member of several other journals, including Information Sciences, Fuzzy Sets and Systems, Journal of Intelligent and Fuzzy Systems, Iranian J. of Fuzzy Systems and Mathematical Sciences. Dr. Witold Pedrycz (IEEE Fellow, 1998) is Professor and Canada Research Chair (CRC) in computational intelligence in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. In 2012 he was elected a fellow of the Royal Society of Canada. His main research directions involve computational intelligence, fuzzy modeling and granular computing, knowledge discovery and data science, pattern recognition, data science, knowledge-based neural networks, and control engineering. He is also an author of 18 research monographs and edited volumes covering various aspects of computational intelligence, data mining, and software engineering. Dr. Pedrycz is vigorously involved in editorial activities. He is the editor-in-chief of Information Sciences, editor-in-chief of WIREs Data Mining and Knowledge Discovery, and co-editor-in-chief of International Journal of Granular Computing, and Journal of Data Information and Management. He serves on the advisory board of IEEE Transactions on Fuzzy Systems. Amir Seyyedabbasi is an assistant professor of software engineering at Istinye University, Turkey. He received his B.Sc., M.Sc., and Ph.D. degrees in computer engineering. His research interests include optimization algorithms, routing protocol design in wireless sensor networks, and IoT. Dr. Seyyedabbasi has several articles in Springer and Elsevier. He serves as a reviewer in some respected journals. He aims to develop and propose new and the hybrid optimization algorithm in engineering.
