Available:*
Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
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Searching... | 30000010099139 | QA76.9.S63 F89 2005 | Open Access Book | Book | Searching... |
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Summary
Summary
This book is devoted to reporting innovative and significant progress in fuzzy system engineering. Given the maturation of fuzzy logic, this book is dedicated to exploring the recent breakthroughs in fuzziness and soft computing in favour of intelligent system engineering. This monograph presents novel developments of the fuzzy theory as well as interesting applications of the fuzzy logic exploiting the theory to engineer intelligent systems.
Reviews 1
Choice Review
Ever since its inception in the 1960s, fuzzy logic has contributed to the introduction of new methodologies and more anthropomorphic approaches to solving a myriad of engineering problems. As it has matured, it has changed the way we think about and approach intelligent system engineering. This volume by Nedjah and Mourelle (both, Universidade do Estado do Rio de Janeiro, Brazil) is a tribute to several recent developments in this area. Namely, it is an overview of a recent breakthrough in the field of fuzzy systems engineering. The book is organized in two parts: "Fuzzy Theory" and "Fuzzy Systems." The chapters are well organized and self-contained, with plentiful examples. The theoretical part of the book introduces the fundamentals of fuzziness, proposes a qualitative approach to symbolic data manipulation, and offers a selection of fuzzy inference systems using artificial neural networks. The systems section focuses on fuzzy control in interception flights, monitoring systems, servo-control systems, mobile robotic systems, and chemical process reactors. Not only is this book easy to read and follow, with interesting new results, it is well-rounded reading for anyone considering investigating engineering phenomena using fuzzy tools. And a good read, too. ^BSumming Up: Highly recommended. Upper-division undergraduates through faculty and researchers. G. Trajkovski Towson University
Table of Contents
Part I Fuzzy Theory |
Introducing You to Fuzziness |
A Qualitative Approach for Symbolic Data Manipulation Under Uncertainty |
Adaptation of Fuzzy Inference System Using Neural Learning |
Part II Fuzzy Systems |
A fuzzy approach on guiding model for interception flight |
On the Stability and Sensitivity Analysis of Fuzzy Control Systems for Servo-systems |
Applications of Fuzzy Logic in Mobile Robots Control |
Modeling the Tennessee Eastman Chemical Process Reactor Using Fuzzy Logic |