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Fuzzy logic for business, finance, and management / with a foreword by Lofti A. Zadeh ; George Bojadziev, Maria Bojadziev.
1997
B 70 BOJ.F
Available at WIPO Library
Items
Details
Title
Fuzzy logic for business, finance, and management / with a foreword by Lofti A. Zadeh ; George Bojadziev, Maria Bojadziev.
Author
Bojadziev, George, author.
Bojadziev, Maria, author.
Zadeh, Lotfi Asker.
Scientific, World (Firm)
Bojadziev, Maria, author.
Zadeh, Lotfi Asker.
Scientific, World (Firm)
Description
xviii, 232 pages : illustrations ; 23 cm.
ISBN
9810228945
9789812819789 electronic book
9789810228941
9789812819789 electronic book
9789810228941
Alternate Call Number
B 70 BOJ.F
Summary
This is an interdisciplinary book for knowledge workers in business, finance, management, and socio-economic sciences. It provides a guide to and techniques for forecasting, decision making, conclusions, and evaluations in an environment involving uncertainty, vagueness, and impression. Traditional modeling techniques do not capture the nature of complex systems especially when humans are involved. Fuzzy logic provides effective tools for dealing with such systems. Emphasis is on applications presented in case studies including Time Forecasting for Project Management, New Product Pricing, Client Financial Risk Tolerance Policy, Deviation and Potential Problem Analysis, Inventory Control Model, Stock Market Strategy.
Note
Price : US$ 42.00; Inv.# Supplier : Amazon.Com, Seattle, WA; Recd 14/09/98; Contents : 1. Fuzzy sets; 2. Fuzzy logic; 3. Fuzzy averaging for forecasting; 4. Decision making in a fuzzy environment; 5. Fuzzy logic control for business, finance, and management; 6. Applications of fuzzy logic control; 7. Fuzzy queries from databases : applications;.
Bibliography, etc. Note
Includes bibliographical references (pages 217-222) and index.
Formatted Contents Note
1. Fuzzy sets. 1.1. Classical sets: Relations and functions. 1.2. Definition of fuzzy sets. 1.3. Basic operations on fuzzy sets. 1.4. Fuzzy numbers. 1.5. Triangular fuzzy numbers. 1.6. Trapezoidal fuzzy numbers. 1.7. Fuzzy relations. 1.8. Basic operations on fuzzy relations. 1.9. Notes
2. Fuzzy logic. 2.1. Basic concepts of classical logic. 2.2. Many-valued logic. 2.3. What is fuzzy logic? 2.4. Linguistic variables. 2.5. Linguistic modifiers. 2.6. Composition rules for fuzzy propositions. 2.7. Semantic entailment. 2.8. Notes
3. Fuzzy averaging for forecasting. 3.1. Statistical average. 3.2. Arithmetic operations with triangular and trapezoidal numbers. 3.3. Fuzzy averaging. 3.4. Fuzzy delphi method for forecasting. 3.5. Weighted fuzzy delphi method. 3.6. Fuzzy PERT for project management. 3.7. Forecasting demand. 3.8. Notes
4. Decision making in a fuzzy environment. 4.1. Decision making by intersection of fuzzy goals and constraints. 4.2. Various applications. 4.3. Pricing models for new products. 4.4. Fuzzy averaging for decision making. 4.5. Multi-expert decision making. 4.6. Fuzzy zero-based budgeting. 4.7. Notes
5. Fuzzy logic control for business, finance, and management. 5.1. Introduction. 5.2. Modeling the control variables. 5.3. If ... and ... then rules. 5.4. Rule evaluation. 5.5. Aggregation (conflict resolution). 5.6. Defuzzification. 5.7. Use of singletons to model outputs. 5.8. Tuning of fuzzy logic control models. 5.9. One-input-one-output control model. 5.10. Notes
6. Applications of fuzzy logic control. 6.1. Investment advisory models. 6.2. Fuzzy logic control for pest management. 6.3. Inventory control models. 6.4. Problem analysis. 6.5. Potential problem analysis. 6.6. Notes
7. Fuzzy queries from databases: Applications. 7.1. Standard relational databases. 7.2. Fuzzy queries. 7.3. Fuzzy complex queries. 7.4. Fuzzy queries for small manufacturing companies. 7.5. Fuzzy queries for stocks and funds databases. 7.6. Notes.
2. Fuzzy logic. 2.1. Basic concepts of classical logic. 2.2. Many-valued logic. 2.3. What is fuzzy logic? 2.4. Linguistic variables. 2.5. Linguistic modifiers. 2.6. Composition rules for fuzzy propositions. 2.7. Semantic entailment. 2.8. Notes
3. Fuzzy averaging for forecasting. 3.1. Statistical average. 3.2. Arithmetic operations with triangular and trapezoidal numbers. 3.3. Fuzzy averaging. 3.4. Fuzzy delphi method for forecasting. 3.5. Weighted fuzzy delphi method. 3.6. Fuzzy PERT for project management. 3.7. Forecasting demand. 3.8. Notes
4. Decision making in a fuzzy environment. 4.1. Decision making by intersection of fuzzy goals and constraints. 4.2. Various applications. 4.3. Pricing models for new products. 4.4. Fuzzy averaging for decision making. 4.5. Multi-expert decision making. 4.6. Fuzzy zero-based budgeting. 4.7. Notes
5. Fuzzy logic control for business, finance, and management. 5.1. Introduction. 5.2. Modeling the control variables. 5.3. If ... and ... then rules. 5.4. Rule evaluation. 5.5. Aggregation (conflict resolution). 5.6. Defuzzification. 5.7. Use of singletons to model outputs. 5.8. Tuning of fuzzy logic control models. 5.9. One-input-one-output control model. 5.10. Notes
6. Applications of fuzzy logic control. 6.1. Investment advisory models. 6.2. Fuzzy logic control for pest management. 6.3. Inventory control models. 6.4. Problem analysis. 6.5. Potential problem analysis. 6.6. Notes
7. Fuzzy queries from databases: Applications. 7.1. Standard relational databases. 7.2. Fuzzy queries. 7.3. Fuzzy complex queries. 7.4. Fuzzy queries for small manufacturing companies. 7.5. Fuzzy queries for stocks and funds databases. 7.6. Notes.
Series
Advances in fuzzy systems ; v. 12.
Published
Singapore : World Scientific, c1997.
Language
English
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