书名 Fuzzy Logic for Business, Finance, and Management (2nd Edition)<br/><br/>作者 George Bojadziev, Maria Bojadziev<br/><br/>各式 PDF <br/><br/>页码 253<br/>Contents<br/>Foreword xi<br/>Preface to the Second Edition xiii<br/>Preface to the First Edition xv<br/>List of Case Studies xix<br/>1 Fuzzy Sets 1<br/>1.1 Classical Sets: Relations and Functions . . . . . . . . . 1<br/>1.2 Denition of Fuzzy Sets . . . . . . . . . . . . . . . . . . 9<br/>1.3 Basic Operations on Fuzzy Sets . . . . . . . . . . . . . . 15<br/>1.4 Fuzzy Numbers . . . . . . . . . . . . . . . . . . . . . . . 19<br/>1.5 Triangular Fuzzy Numbers . . . . . . . . . . . . . . . . . 22<br/>1.6 Trapezoidal Fuzzy Numbers . . . . . . . . . . . . . . . . 24<br/>1.7 Fuzzy Relations . . . . . . . . . . . . . . . . . . . . . . . 26<br/>1.8 Basic Operations on Fuzzy Relations . . . . . . . . . . . 29<br/>1.9 Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32<br/>2 Fuzzy Logic 37<br/>2.1 Basic Concepts of Classical Logic . . . . . . . . . . . . . 37<br/>2.2 Many-Valued Logic . . . . . . . . . . . . . . . . . . . . . 41<br/>2.3 What is Fuzzy Logic? . . . . . . . . . . . . . . . . . . . 43<br/>2.4 Linguistic Variables . . . . . . . . . . . . . . . . . . . . . 44<br/>2.5 Linguistic Modiers . . . . . . . . . . . . . . . . . . . . 46<br/>2.6 Composition Rules for Fuzzy Propositions . . . . . . . . 50<br/>2.7 Semantic Entailment . . . . . . . . . . . . . . . . . . . . 54<br/>2.8 Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56<br/><br/>3 Fuzzy Averaging for Forecasting 61<br/>3.1 Statistical Average . . . . . . . . . . . . . . . . . . . . . 61<br/>3.2 Arithmetic Operations with Triangular and Trapezoidal<br/>Numbers . . . . . . . . . . . . . . . . . . . . . . . . . . . 62<br/>3.3 Fuzzy Averaging . . . . . . . . . . . . . . . . . . . . . . 66<br/>3.4 Fuzzy Delphi Method for Forecasting . . . . . . . . . . . 71<br/>3.5 Weighted Fuzzy Delphi Method . . . . . . . . . . . . . . 76<br/>3.6 Fuzzy PERT for Project Management . . . . . . . . . . 77<br/>3.7 Forecasting Demand . . . . . . . . . . . . . . . . . . . . 87<br/>3.8 Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89<br/>4 Decision Making in a Fuzzy Environment 91<br/>4.1 Decision Making by Intersection of Fuzzy Goals and Con-<br/>straints . . . . . . . . . . . . . . . . . . . . . . . . . . . 92<br/>4.2 Various Applications . . . . . . . . . . . . . . . . . . . . 95<br/>4.3 Pricing Models for New Products . . . . . . . . . . . . . 104<br/>4.4 Fuzzy Averaging for Decision Making . . . . . . . . . . 110<br/>4.5 Multi-Expert Decision Making . . . . . . . . . . . . . . 115<br/>4.6 Fuzzy Zero-Based Budgeting . . . . . . . . . . . . . . . 119<br/>4.7 Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125<br/>5 Fuzzy Logic Control for Business, Finance, and Manage-<br/>ment 127<br/>5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 127<br/>5.2 Modeling the Control Variables . . . . . . . . . . . . . . 129<br/>5.3 If : : : and : : : Then Rules . . . . . . . . . . . . . . . . . . 133<br/>5.4 Rule Evaluation . . . . . . . . . . . . . . . . . . . . . . . 136<br/>5.5 Aggregation (Con<br/>ict Resolution) . . . . . . . . . . . . . 138<br/>5.6 Defuzzication . . . . . . . . . . . . . . . . . . . . . . . 144<br/>5.7 Use of Singletons to Model Outputs . . . . . . . . . . . 149<br/>5.8 Tuning of Fuzzy Logic Control Models . . . . . . . . . . 150<br/>5.9 One-Input{One-Output Control Model . . . . . . . . . . 152<br/>5.10 Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155<br/>6 Applications of Fuzzy Logic Control 157<br/>6.1 Investment Advisory Models . . . . . . . . . . . . . . . . 157<br/>6.2 Fuzzy Logic Control for Pest Management . . . . . . . . 164<br/>6.3 Inventory Control Models . . . . . . . . . . . . . . . . . 170<br/>6.4 Problem Analysis . . . . . . . . . . . . . . . . . . . . . . 177<br/>6.5 Potential Problem Analysis . . . . . . . . . . . . . . . . 182<br/>6.6 Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185<br/>7 Fuzzy Queries from Databases: Applications 187<br/>7.1 Standard Relational Databases . . . . . . . . . . . . . . 187<br/>7.2 Fuzzy Queries . . . . . . . . . . . . . . . . . . . . . . . . 190<br/>7.3 Fuzzy Complex Queries . . . . . . . . . . . . . . . . . . 196<br/>7.4 Fuzzy Queries for Small Manufacturing Companies . . . 199<br/>7.5 Fuzzy Queries for Stocks and Funds Databases . . . . . 206<br/>7.6 Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215<br/>References 217<br/>Index 223<br/><br/>