Fuzzy Logic with Engineering Applications, 4th Edition

Fuzzy Logic with Engineering Applications, 4th Edition

by Timothy J. Ross
Released October 2016
Publisher(s): Wiley
ISBN: 9781119235866

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Book description

Fuzzy Logic with Engineering Applications, Fourth Edition

Timothy J. Ross, University of New Mexico, USA

 

The latest update on this popular textbook

 

The importance of concepts and methods based on fuzzy logic and fuzzy set theory has been rapidly growing since the early 1990s and all the indications are that this trend will continue in the foreseeable future. Fuzzy Logic with Engineering Applications, Fourth Edition is a new edition of the popular textbook with 15% of new and updated material. Updates have been made to most of the chapters and each chapter now includes new end-of-chapter problems.

 

 

Key features:

  • New edition of the popular textbook with 15% of new and updated material.
  • Includes new examples and end-of-chapter problems.
  • Has been made more concise with the removal of out of date material.
  • Covers applications of fuzzy logic to engineering and science.
  • Accompanied by a website hosting a solutions manual and software.

 

 

The book is essential reading for graduates and senior undergraduate students in civil, chemical, mechanical and electrical engineering as wells as researchers and practitioners working with fuzzy logic in industry.

Table of contents

  1. Cover
  2. Title Page
  3. About the Author
  4. Preface to the Fourth Edition
  5. 1 Introduction
    1. The Case for Imprecision
    2. A Historical Perspective
    3. The Utility of Fuzzy Systems
    4. Limitations of Fuzzy Systems
    5. The Illusion: Ignoring Uncertainty and Accuracy
    6. Uncertainty and Information
    7. Fuzzy Sets and Membership
    8. Chance versus Fuzziness
    9. Intuition of Uncertainty: Fuzzy versus Probability
    10. Sets as Points in Hypercubes
    11. Summary
    12. References
    13. Problems
  6. 2 Classical Sets and Fuzzy Sets
    1. Classical Sets
    2. Fuzzy Sets
    3. Summary
    4. References
    5. Problems
  7. 3 Classical Relations and Fuzzy Relations
    1. Cartesian Product
    2. Crisp Relations
    3. Fuzzy Relations
    4. Tolerance and Equivalence Relations
    5. Fuzzy Tolerance and Equivalence Relations
    6. Value Assignments
    7. Other Forms of the Composition Operation
    8. Summary
    9. References
    10. Problems
  8. 4 Properties of Membership Functions, Fuzzification, and Defuzzification
    1. Features of the Membership Function
    2. Various Forms
    3. Fuzzification
    4. Defuzzification to Crisp Sets
    5. λ‐Cuts for Fuzzy Relations
    6. Defuzzification to Scalars
    7. Summary
    8. References
    9. Problems
  9. 5 Logic and Fuzzy Systems
    1. Part I: Logic
    2. Classical Logic
    3. Fuzzy Logic
    4. Part II: Fuzzy Systems
    5. Summary
    6. References
    7. Problems
  10. 6 Historical Methods of Developing Membership Functions
    1. Membership Value Assignments
    2. Intuition
    3. Inference
    4. Rank Ordering
    5. Neural Networks
    6. Genetic Algorithms
    7. Inductive Reasoning
    8. Summary
    9. References
    10. Problems
  11. 7 Automated Methods for Fuzzy Systems
    1. Definitions
    2. Batch Least Squares Algorithm
    3. Recursive Least Squares Algorithm
    4. Gradient Method
    5. Clustering Method
    6. Learning from Examples
    7. Modified Learning from Examples
    8. Summary
    9. References
    10. Problems
  12. 8 Fuzzy Systems Simulation
    1. Fuzzy Relational Equations
    2. Nonlinear Simulation Using Fuzzy Systems
    3. Fuzzy Associative Memories (FAMs)
    4. Summary
    5. References
    6. Problems
  13. 9 Decision Making with Fuzzy Information
    1. Fuzzy Synthetic Evaluation
    2. Fuzzy Ordering
    3. Nontransitive Ranking
    4. Preference and Consensus
    5. Multiobjective Decision Making
    6. Fuzzy Bayesian Decision Method
    7. Decision Making under Fuzzy States and Fuzzy Actions
    8. Summary
    9. References
    10. Problems
  14. 10 Fuzzy Classification and Pattern Recognition
    1. Fuzzy Classification
    2. Classification by Equivalence Relations
    3. Cluster Analysis
    4. Cluster Validity
    5. c‐Means Clustering
    6. Hard c‐Means (HCM)
    7. Fuzzy c‐Means (FCM)
    8. Classification Metric
    9. Hardening the Fuzzy c‐Partition
    10. Similarity Relations from Clustering
    11. Fuzzy Pattern Recognition
    12. Single‐Sample Identification
    13. Multifeature Pattern Recognition
    14. Summary
    15. References
    16. Problems
  15. 11 Fuzzy Control Systems
    1. Control System Design Problem
    2. Examples of Fuzzy Control System Design
    3. Fuzzy Engineering Process Control
    4. Fuzzy Statistical Process Control
    5. Industrial Applications
    6. Summary
    7. References
    8. Problems
  16. 12 Applications of Fuzzy Systems Using Miscellaneous Models
    1. Fuzzy Optimization
    2. Fuzzy Cognitive Mapping
    3. Agent‐Based Models
    4. Fuzzy Arithmetic and the Extension Principle
    5. Fuzzy Algebra
    6. Data Fusion
    7. Summary
    8. References
    9. Problems
  17. 13 Monotone Measures
    1. Monotone Measures
    2. Belief and Plausibility
    3. Evidence Theory
    4. Probability Measures
    5. Possibility and Necessity Measures
    6. Possibility Distributions as Fuzzy Sets
    7. Possibility Distributions Derived from Empirical Intervals
    8. Summary
    9. References
    10. Problems
  18. Index
  19. End User License Agreement

Product information

  • Title: Fuzzy Logic with Engineering Applications, 4th Edition
  • Author(s): Timothy J. Ross
  • Release date: October 2016
  • Publisher(s): Wiley
  • ISBN: 9781119235866