Computer Science

Soft Computing and Its Applications: Volume 2
Fuzzy Reasoning and Fuzzy Control

Kumar S. Ray, PhD

Soft Computing and Its Applications: Volume 2

Published. Available now.
Pub Date: September 2014
Hardback Price: $199.95 US
Hard ISBN: 9781771880466
Pages: 468pp + Index
Binding Type: hardbound

“Comprehensive introduction of soft computing, accessible not only for undergraduates in mathematics but also for students in computer science and engineering . . . Offers figures for most notations 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 and fuzzy relations, on fuzzy logic, on fuzzy implications and fuzzy if-then models, and on rough sets. Volume 2 covers in separate chapters the topics of fuzzy reasoning, of fuzzy reasoning based on the concept of similarity, and of fuzzy control. The author included also more recent and, occasionally, a bit more advanced topics.”
—Siegfried J. Gottwald (Leipzig), in Zentralblatt MATH 1308

This is volume 2 of the two-volume Soft Computing and Its Applications. This volume discusses several advanced features of soft computing and hybrid methodologies. This new book essentially contains the advanced features of soft computing and different hybrid methodologies for soft computing. The book contains an abundance of examples and detailed design studies.

The tool soft computing can be a landmark paradigm of computation with cognition that directly or indirectly tries to replicate the rationality of human beings. The book explains several advanced features of soft computing, such as cognitive maps, complex valued fuzzy sets and fuzzy logic, quantum fuzzy sets and quantum fuzzy logic, and rough sets and hybrid methods that combine neural net fuzzy logic and genetic algorithms. The book contains several real-life applications to present the utility and potential of soft computing.

The book
  • discuss the present state of art of soft computing
  • include the existing application areas of soft computing
  • present original research contributions
  • discuss the future scope of work in soft computing
The book is unique in that it bridges the gap between theory and practice, and it presents several experimental results on synthetic data and real life data. The book provides a unified platform for applied scientists and engineers in different fields and industries for the application of soft computing tools in many diverse domains of engineering. This book can be used as a textbook and/or reference book by undergraduate and postgraduate students of many different engineering branches, such as, for example, electrical engineering, control engineering, electronics and communication engineering, computer sciences, and information sciences.

Click here for information on Volume 1.

See information on the complete set here:


Chapter 1. Fuzzy Reasoning
- 1.1. Introduction
- 1.2. Model of approximate reasoning
- 1.3. Basic approach to Zadeh’s fuzzy reasoning
- 1.4. Extended fuzzy reasoning
- 1.5. Further extension of fuzzy reasoning
- 1.6. Generalized form of fuzzy reasoning
- 1.7. Application of fuzzy reasoning for prediction of radiation fog
- 1.8. Aggregation in fuzzy system modeling
- 1.9. Single Input Rule Modules (SIRMs) connected fuzzy reasoning method
- 1.10. Some properties of compositional rule of inference
- 1.11. Computation of compositional rule of inference under t-norms
- 1.12. Inverse approximate reasoning
- 1.13. Interpolative fuzzy reasoning
- 1.14. On generalized method-of-case inference rule
- 1.15. Generalized disjunctive syllogism
- 1.16. Ray’s bottom-up inferences
- 1.17. Multidimensional fuzzy reasoning based on multidimensional fuzzy implication
Chapter 2. Fuzzy Reasoning Based on Concept of Similarity
- 2.1. Introduction
- 2.2. Fuzzy reasoning using similarity
- 2.3. Similarity based fuzzy reasoning method
- 2.4. Rule reduction is SBR
- 2.5. Proposed similarity measure
- 2.6. Fuzzy reasoning using similarity measures and computational rule of inference
- 2.7. Applications to different models
- 2.8. Reasoning based on total fuzzy similarity
- 2.9. Similarity-based bidirectional approximate reasoning
- 2.10. Logical approaches to fuzzy similarity-based reasoning
- 2.11. Fuzzy resolution based on similarity-based unification
Chapter 3. Fuzzy Control
- 3.1. Introduction
- 3.2. Fuzzy controller
- 3.3. Illustration on basic approaches to fuzzy control
- 3.3.1. Fuzzy associative memory
- 3.4. Fuzzy controller design
- 3.5. Adaptive fuzzy controller design
- 3.6 Self-tuning of fuzzy controller
- 3.7. Single input rule module (SIRM)
- 3.8. Construction of PID controller by simplified fuzzy reasoning method
- 3.9. Fuzzy control as a fuzzy deduction system
Chapter 4. Concluding Remarks
- 4.1. Review of the applications and future scope

About the Authors / Editors:
Kumar S. Ray, PhD
Professor, Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India

Kumar S. Ray, PhD, is a professor in the Electronics and Communication Science Unit at the Indian Statistical Institute, Kolkata, India. He is an alumnus of University of Bradford, UK. He was a visiting faculty member under a fellowship program at the University of Texas, Austin, USA. Professor Ray was a member of task force committee of the Government of India, Department of Electronics (DoE/MIT), for the application of AI in power plants. He is the founder and member of Indian Society for Fuzzy Mathematics and Information Processing (ISFUMIP) and a member of Indian Unit for Pattern Recognition and Artificial Intelligence (IUPRAI). In 1991, he was the recipient of the K. S. Krishnan memorial award for the best system-oriented paper in computer vision. He has written a number of research articles published in international journals and has presented at several professional meetings. He also serves as a reviewer of several International journals.

His current research interests include artificial intelligence, computer vision, commonsense reasoning, soft computing, non-monotonic deductive database systems, and DNA computing.

He is the co-author of two edited volumes on approximate reasoning and fuzzy logic and fuzzy computing, and he is the co-author of Case Studies in Intelligent Computing-Achievements and Trends. He has is also the author of Polygonal Approximation and Scale-Space Analysis of Closed Digital Curves,published Apple Academic Press, Inc.

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