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Full Description
Mathematical Modeling using Fuzzy Logic has been a dream project for the author. Fuzzy logic provides a unique method of approximate reasoning in an imperfect world. This text is a bridge to the principles of fuzzy logic through an application-focused approach to selected topics in engineering and management. The many examples point to the richer solutions obtained through fuzzy logic and to the possibilities of much wider applications. There are relatively very few texts available at present in fuzzy logic applications. The style and content of this text is complementary to those already available. New areas of application, like application of fuzzy logic in modeling of sustainability, are presented in a graded approach in which the underlying concepts are first described. The text is broadly divided into two parts: the first treats processes, materials, and system applications related to fuzzy logic, and the second delves into the modeling of sustainability with the help of fuzzy logic.
This book offers comprehensive coverage of the most essential topics, including:
Treating processes, materials, system applications related to fuzzy logic
Highlighting new areas of application of fuzzy logic
Identifying possibilities of much wider applications of fuzzy logic
Modeling of sustainability with the help of fuzzy logic
The level enables a selection of the text to be made for the substance of undergraduate-, graduate-, and postgraduate-level courses. There is also sufficient volume and quality for the basis of a postgraduate course. A more restricted and judicious selection can provide the material for a professional short course and various university-level courses.
Contents
Preface. Acknowledgments. Author. 1. Introduction. 2. Sources of Uncertainty. 3. Membership Functions and Uncertainty. 4. Case Studies. 5. Singleton Type 1 Fuzzy Logic Systems: No Uncertainties. 6. Centroid of a Type 2 Fuzzy Set: Type Reduction. 7. Modeling of Sustainability. 8. Epilogue. Appendix A: Join, Meet, and Negation Operations for Non-Interval Type 2 Fuzzy Sets. Appendix B: Properties of Type 1 and Type 2 Fuzzy Sets. Appendix C: Computation. Appendix D: Medical Diagnosis by Fuzzy Logic. Appendix E: Fuzzy Logic System Optimized. Appendix F: Heart Disease Demo. Appendix G: Linear Tip Demo, Mamdani Tip Demo, Sugeno Tip Demo. Appendix H: Miscellaneous. Index.
