1st Edition
Soft Computing and Its Applications, Volume Two Fuzzy Reasoning and Fuzzy Control
Fuzzy Reasoning
Introduction
Model of approximate reasoning
Basic approach to Zadeh’s fuzzy reasoning
Extended fuzzy reasoning
Further extension of fuzzy reasoning
Generalized form of fuzzy reasoning
Application of fuzzy reasoning for prediction of radiation fog
Aggregation in fuzzy system modeling
Single Input Rule Modules (SIRMs) connected fuzzy reasoning method
Some properties of compositional rule of inference
Computation of compositional rule of inference under t-norms
Inverse approximate reasoning
Interpolative fuzzy reasoning
On generalized method-of-case inference rule
Generalized disjunctive syllogism
Ray’s bottom-up inferences
Multidimensional fuzzy reasoning based on multidimensional fuzzy implication
Fuzzy Reasoning Based on Concept of Similarity
Introduction
Fuzzy reasoning using similarity
Similarity based fuzzy reasoning method
Rule reduction is SBR
Proposed similarity measure
Fuzzy reasoning using similarity measures and computational rule of inference
Applications to different models
Reasoning based on total fuzzy similarity
Similarity-based bidirectional approximate reasoning
Logical approaches to fuzzy similarity-based reasoning
Fuzzy resolution based on similarity-based unification
Fuzzy Control
Introduction
Fuzzy controller
Illustration on basic approaches to fuzzy control
Fuzzy associative memory
Fuzzy controller design
Adaptive fuzzy controller design
Self-tuning of fuzzy controller
Single input rule module (SIRM)
Construction of PID controller by simplified fuzzy reasoning method
Fuzzy control as a fuzzy deduction system
Concluding Remarks
Review of the applications and future scope
Index
Biography
Kumar S. Ray, PhD, is a professor in the Electronics and Communication Science Unit at the Indian Statistical Institute, Kolkata, India. He has written a number of articles published in international journals and has presented at several professional meetings. His current research interests include artificial intelligence, computer vision, commonsense reasoning, soft computing, non-monotonic deductive database systems, and DNA computing.
"This two-volume textbook set is a quite elementary, but rather comprehensive, introduction to the field of soft computing, accessible not only for undergraduates in mathematics, but also for students in computer science and engineering. The presentation is essentially correct, offers figures for most of the notions it defines, and presents lots of detailed numerical examples. Volume 1 starts with an explanation of the notion of soft computing and continues with chapters on fuzzy sets, fuzzy operators, fuzzy relations, fuzzy logic, fuzzy implications, fuzzy if-then models, and rough sets. Volume 2 covers in separate chapters the topics of fuzzy reasoning, fuzzy reasoning based on the concept of similarity, and fuzzy control."
—Siegfried J. Gottwald, writing in Zentralblatt MATH, 1308
