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.
About the author
Witold Pedrycz, Ph D, 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, Ph D, 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.
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