Mathematical Modeling Using Fuzzy Logic - Info and Reading Options

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Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Acknowledgments -- Author -- 1. Introduction -- 1.1 Rule-Based Fuzzy Logic Systems -- 1.2 A New Direction for FLSs -- 1.3 New Concepts and Their Historical Background -- 1.4 Fundamental Diamond Requirement -- 1.5 The Flow of Uncertainties -- 1.6 Existing Literature on Type 2 Fuzzy Sets -- 1.7 Coverage -- 1.8 Applicability Outside of Rule-Based FLS -- 1.9 Computation -- 1.10 Primer on Fuzzy Sets -- 1.10.1 Fuzzy Sets -- 1.10.2 From Fuzzy Sets to Crisp Sets -- 1.10.3 Linguistic Variables -- 1.10.4 Membership Functions -- 1.10.5 Some Terminology -- 1.10.6 Set-Theoretic Operations on Crisp Sets -- 1.10.7 Set-Theoretic Operations for Fuzzy Sets -- 1.10.8 Crisp Relations and Compositions on the Same Product Space -- 1.10.9 Relations and Compositions -- 1.10.10 Hedges -- 1.10.11 Expansion Principle -- 1.11 FL Primer -- 1.11.1 Crisp Logic -- 1.11.2 From Crisp Logic to FL -- 1.12 Remarks -- 1.13 Exercise -- References -- 2. Sources of Uncertainty -- 2.1 Uncertainty -- 2.1.1 Uncertainty: General Discussion -- 2.1.2 Uncertainty at FLS -- 2.2 Words Mean Different Things to Different People -- 2.3 Exercise -- References -- 3. Membership Functions and Uncertainty -- 3.1 Introduction -- 3.2 Type 1 Membership Function -- 3.2.1 The Concept of a Type 2 Fuzzy Set -- 3.2.2 Definition of Type 2 Fuzzy Sets and Related Concepts -- 3.2.3 Type 2 Fuzzy Sets and Examples of FOU -- 3.2.4 Upper and Lower Membership Functions -- 3.2.5 A Type 1 Purge Set Represented by a Type 2 Fuzzy Set -- 3.2.6 0 and 1 Membership of Type 2 Fuzzy Set -- 3.3 Back to the Language Label -- 3.4 Exercise -- References -- 4. Case Studies -- 4.1 Introduction -- 4.2 Time Series Prediction -- 4.2.1 Extracting Rules from Data -- 4.2.2 Classic Time Series Forecasting Method -- 4.2.2.1 Autoregression (AR)

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