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E-raamat: Fuzzy Logic For Business, Finance, And Management (2nd Edition)

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(British Columbia Inst Of Technology, Canada), (Simon Fraser Univ, Canada)
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This is truly an interdisciplinary book for knowledge workers in business, finance, management and socio-economic sciences based on fuzzy logic. It serves as a guide to and techniques for forecasting, decision making and evaluations in an environment involving uncertainty, vagueness, impression and subjectivity. Traditional modeling techniques, contrary to fuzzy logic, do not capture the nature of complex systems especially when humans are involved. Fuzzy logic uses human experience and judgement to facilitate plausible reasoning in order to reach a conclusion. Emphasis is on applications presented in the 27 case studies including Time Forecasting for Project Management, New Product Pricing, and Control of a Parasit-Pest System.
Foreword xi
Preface to the Second Edition xiii
Preface to the First Edition xv
List of Case Studies xix
1 Fuzzy Sets 1
1.1 Classical Sets: Relations and Functions
1
1.2 Definition of Fuzzy Sets
9
1.3 Basic Operations on Fuzzy Sets
15
1.4 Fuzzy Numbers
19
1.5 Triangular Fuzzy Numbers
22
1.6 Trapezoidal Fuzzy Numbers
24
1.7 Fuzzy Relations
26
1.8 Basic Operations on Fuzzy Relations
29
1.9 Notes
32
2 Fuzzy Logic 37
2.1 Basic Concepts of Classical Logic
37
2.2 Many-Valued Logic
41
2.3 What is Fuzzy Logic?
43
2.4 Linguistic Variables
44
2.5 Linguistic Modifiers
46
2.6 Composition Rules for Fuzzy Propositions
50
2.7 Semantic Entailment
54
2.8 Notes
56
3 Fuzzy Averaging for Forecasting 61
3.1 Statistical Average
61
3.2 Arithmetic Operations with Triangular and Trapezoidal Numbers
62
3.3 Fuzzy Averaging
66
3.4 Fuzzy Delphi Method for Forecasting
71
3.5 Weighted Fuzzy Delphi Method
76
3.6 Fuzzy PERT for Project Management
77
3.7 Forecasting Demand
87
3.8 Notes
89
4 Decision Making in a Fuzzy Environment 91
4.1 Decision Making by Intersection of Fuzzy Goals and Constraints
92
4.2 Various Applications
95
4.3 Pricing Models for New Products
104
4.4 Fuzzy Averaging for Decision Making
110
4.5 Multi-Expert Decision Making
115
4.6 Fuzzy Zero-Based Budgeting
119
4.7 Notes
125
5 Fuzzy Logic Control for Business, Finance, and Management 127
5.1 Introduction
127
5.2 Modeling the Control Variables
129
5.3 If...and...Then Rules
133
5.4 Rule Evaluation
136
5.5 Aggregation (Conflict Resolution)
138
5.6 Defuzzification
144
5.7 Use of Singletons to Model Outputs
149
5.8 Tuning of Fuzzy Logic Control Models
150
5.9 One-Input-One-Output Control Model
152
5.10 Notes
155
6 Applications of Fuzzy Logic Control 157
6.1 Investment Advisory Models
157
6.2 Fuzzy Logic Control for Pest Management
164
6.3 Inventory Control Models
170
6.4 Problem Analysis
177
6.5 Potential Problem Analysis
182
6.6 Notes
185
7 Fuzzy Queries from Databases: Applications 187
7.1 Standard Relational Databases
187
7.2 Fuzzy Queries
190
7.3 Fuzzy Complex Queries
196
7.4 Fuzzy Queries for Small Manufacturing Companies
199
7.5 Fuzzy Queries for Stocks and Funds Databases
206
7.6 Notes
215
References 217
Index 223


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