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Fuzzy sets and fuzzy logic : theory and applications / George J. Klir and Bo Yuan.

By: Klir, George JiriContributor(s): Yuan, BoMaterial type: TextTextPublication details: Prentice-Hall, 1995. ISBN: 0131011715DDC classification: 511.322
Partial contents:
1. From Classical (Crisp) Sets to Fuzzy Sets: A Grand Paradigm Shift -- 2. Fuzzy Sets Versus Crisp Sets -- 3. Operations on Fuzzy Sets -- 4. Fuzzy Arithmetic -- 5. Fuzzy Relations -- 6. Fuzzy Relation Equations -- 7. Possibility Theory -- 8. Fuzzy Logic -- 9. Uncertainty-Based Information -- 10. Constructing Fuzzy Sets and Operations on Fuzzy Sets -- 11. Approximate Reasoning -- 12. Fuzzy Systems -- 13. Pattern Recognition -- 14. Fuzzy Databases and Information Retrieval Systems -- 15. Fuzzy Decision Making -- 16. Engineering Applications -- 17. Miscellaneous Applications -- Appendix A. Neural Networks: An Overview -- Appendix B. Genetic Algorithms: An Overview -- Appendix C. Rough Sets Versus Fuzzy Sets -- Appendix D. Proofs of Some Mathematical Theorems -- Appendix E. Glossary of Key Concepts -- Appendix F. Glossary of Symbols.
Summary: The primary purpose of this book is to provide the reader with a comprehensive coverage of theoretical foundations of fuzzy set theory and fuzzy logic, as well as a broad overview of the increasingly important applications of these novel areas of mathematics. Although it is written as a text for a course at the graduate or upper division undergraduate level, the book is also suitable for self-study and for industry-oriented courses of continuing education. No previous knowledge of fuzzy set theory and fuzzy logic is required for understanding the material covered in the book. Although knowledge of basic ideas of classical (nonfuzzy) set theory and classical (two-valued) logic is useful, fundamentals of these subject areas are briefly overviewed in the book. In addition, basic ideas of neural networks, genetic algorithms, and rough sets are also explained. This makes the book virtually self-contained. Throughout the book, many examples are used to illustrate concepts, methods, and generic applications as they are introduced. Each chapter is followed by a set of exercises, which are intended to enhance readers' understanding of the material presented in the chapter. Extensive and carefully selected bibliography, together with bibliographical notes at the end of each chapter and a bibliographical subject index, is an invaluable resource for further study of fuzzy theory and applications.
Holdings
Item type Home library Call number Status Date due Barcode Item holds
Two Week Loan Two Week Loan College Lane Learning Resources Centre
Main Shelves
511.3 KLI (Browse shelf(Opens below)) Available 4403662697
Two Week Loan Two Week Loan College Lane Learning Resources Centre
Main Shelves
511.3 KLI (Browse shelf(Opens below)) Available 4403662703
Two Week Loan Two Week Loan College Lane Learning Resources Centre
Main Shelves
511.3 KLI (Browse shelf(Opens below)) Available 4401303997
Total holds: 0

Enhanced descriptions from Syndetics:

1. From Classical (Crisp) Sets to Fuzzy Sets: A Grand Paradigm Shift -- 2. Fuzzy Sets Versus Crisp Sets -- 3. Operations on Fuzzy Sets -- 4. Fuzzy Arithmetic -- 5. Fuzzy Relations -- 6. Fuzzy Relation Equations -- 7. Possibility Theory -- 8. Fuzzy Logic -- 9. Uncertainty-Based Information -- 10. Constructing Fuzzy Sets and Operations on Fuzzy Sets -- 11. Approximate Reasoning -- 12. Fuzzy Systems -- 13. Pattern Recognition -- 14. Fuzzy Databases and Information Retrieval Systems -- 15. Fuzzy Decision Making -- 16. Engineering Applications -- 17. Miscellaneous Applications -- Appendix A. Neural Networks: An Overview -- Appendix B. Genetic Algorithms: An Overview -- Appendix C. Rough Sets Versus Fuzzy Sets -- Appendix D. Proofs of Some Mathematical Theorems -- Appendix E. Glossary of Key Concepts -- Appendix F. Glossary of Symbols.

The primary purpose of this book is to provide the reader with a comprehensive coverage of theoretical foundations of fuzzy set theory and fuzzy logic, as well as a broad overview of the increasingly important applications of these novel areas of mathematics. Although it is written as a text for a course at the graduate or upper division undergraduate level, the book is also suitable for self-study and for industry-oriented courses of continuing education. No previous knowledge of fuzzy set theory and fuzzy logic is required for understanding the material covered in the book. Although knowledge of basic ideas of classical (nonfuzzy) set theory and classical (two-valued) logic is useful, fundamentals of these subject areas are briefly overviewed in the book. In addition, basic ideas of neural networks, genetic algorithms, and rough sets are also explained. This makes the book virtually self-contained. Throughout the book, many examples are used to illustrate concepts, methods, and generic applications as they are introduced. Each chapter is followed by a set of exercises, which are intended to enhance readers' understanding of the material presented in the chapter. Extensive and carefully selected bibliography, together with bibliographical notes at the end of each chapter and a bibliographical subject index, is an invaluable resource for further study of fuzzy theory and applications.

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