Fuzzy Systems Engineering: Toward Human-Centric Computing (IEEE Press)

A self-contained treatment of fuzzy systems engineering, offering conceptual fundamentals, design methodologies, development guidelines, and carefully selected illustrative material

Forty years have passed since the birth of fuzzy sets, in which time a wealth of theoretical developments, conceptual pursuits, algorithmic environments, and other applications have emerged. Now, this reader-friendly book presents an up-to-date approach to fuzzy systems engineering, covering concepts, design methodologies, and algorithms coupled with interpretation, analysis, and underlying engineering knowledge. The result is a holistic view of fuzzy sets as a fundamental component of computational intelligence and human-centric systems.

Throughout the book, the authors emphasize the direct applicability and limitations of the concepts being discussed, and historical and bibliographical notes are included in each chapter to help readers view the developments of fuzzy sets from a broader perspective. A radical departure from current books on the subject, Fuzzy Systems Engineering presents fuzzy sets as an enabling technology whose impact, contributions, and methodology stretch far beyond any specific discipline, making it applicable to researchers and practitioners in engineering, computer science, business, medicine, bioinformatics, and computational biology. Additionally, three appendices and classroom-ready electronic resources make it an ideal textbook for advanced undergraduate- and graduate-level courses in engineering and science.

Witold Pedrycz, PhD, is Professor and Canada Research Chair in Computational Intelligence at the University of Alberta, Canada. His research interests include granular computing, including fuzzy set technology, neural networks and evolutionary computing, pattern recognition, data mining, and emerging behavior and adaptive systems. He has authored or edited eight books, over 200 papers in journals or volumes, and over forty conference papers. He is a Fellow of the IEEE and IFSA.

Fernando Gomide, PhD, teaches in the Department of Computer Engineering and Industrial Automation at the State University of Campinas (UNICAMP) in São Paulo, Brazil. His areas of interest include fuzzy sets and logic, artificial intelligence, and genetic algorithms.