Soft Computing and its Applications in Business and Economics

• Κύριοι συγγραφείς: Aliev, Rafik Aziz (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Fazlollahi, Bijan (http://id.loc.gov/vocabulary/relators/aut), Aliev, Rashad Rafik (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2004.
• Έκδοση: 1st ed. 2004.
• Σειρά: Studies in Fuzziness and Soft Computing, 157
• Θέματα: Computers.; Applied mathematics.; Engineering mathematics.; Operations research.; Decision making.; Artificial intelligence.; Information technology.; Business-Data processing.; Theory of Computation.; Mathematical and Computational Engineering.; Operations Research/Decision Theory.; Artificial Intelligence.; IT in Business.

 This monograph provides a self-contained exposition of the foundations of soft computing, and presents a vast compendium of its applications to business, finance, decision analysis and economics. It is the first book on applications of soft computing - based hybrid methods combining fuzzy logic, neuro-computing, evolutionary computing, probabilistic computing and chaotic computing in functional areas of business and economics. The applications range from transportation and health case systems to intelligent stock market prediction, risk management systems, and e-commerce. This book is a valuable aid to anyone considering the application of Soft Computing theory and technology to real problems of business and economics and can be used as a basic text for introducing business managers, scientists, teachers and students to Soft Computing technology, enabling them to initiate projects and make applications. 

 1 Introduction to Soft Computing -- 1.1 Basic Concepts of Soft Computing -- 2.2 Combination of Constituents of Soft Computing -- References -- 2. Constituent Methodologies of Soft Computing -- 2.1 Elements of Fuzzy Sets Theory -- 2.2 Foundations of Neurocomputing -- 2.3 Probabilistic Computing -- 2.4 Evolutionary Computing -- 2.5 Chaotic Computing -- References -- 3. Emerging Combined Soft Computing Technologies -- 3.1 Neuro-Fuzzy Technology -- 3.2 Neuro-Genetic Approach -- 3.3 Fuzzy Genetic Paradigm -- 3.4 Genetic Algorithms with Fuzzy Logic -- 3.5 Neuro-Fuzzy-Genetic Paradigm -- 3.6 Multi-Agent Distributed Intelligent Systems Paradigm -- 3.7 Computing with Words Technology -- References -- 4. Soft Computing Technologies in Business and Economic Forecasting -- 4.1 Neuro-Computing and Forecasting -- 4.2 Fuzzy Time Series Based Forecasting -- 4.3 Fuzzy Delphi Method -- 4.4 Soft Computing Based Forecasting Complex Time Series -- 4.5 Soft Computing Based Prediction Ensemble for Forecasting in Chaotic Time Series -- References -- 5 Soft Computing Based Decision Making and DSS -- 5.1 Fuzzy Linear Programming -- 5.2 Evolutionary Algorithm Based Fuzzy Linear Programming -- 5.3 Fuzzy Chaos Approach to Fuzzy Linear Programming Problem -- 5.4 Fuzzy-Probabilistic Scheduling for Oil Refinery -- 5.5 Fuzzy Decision Making -- 5.6 Multi-Agent Distributed Intelligent System Based on Fuzzy Decision Making -- 5.7 Soft Computing and Data Mining -- 5.8 Soft Computing Based Multi-Agent Marketing DSS -- 5.9 Hybrid DSS Based on Simulation and Genetic Algorithms -- 5.10 Soft Computing Based Alternatives Generations by Decision Support Systems -- References -- 6 Soft Computing in Marketing -- 6.1 Marketing Analysis of a Customer's Purchasing Behavior -- 6.2 Customer Credit Evaluation -- 6.3 Soft Computing Based Fraud Detection -- 6.4 Fuzzy Evaluation of Service Quality -- 6.5 Application of Fuzzy Programming to Hospital's Service Performance Evaluating -- References -- 7 Soft Computing Applications in Operations Management -- 7.1 Application of Fuzzy Logic in Transportation Logistics -- 7.2 Scheduling Fuzzy Expert Systems with Probabilistic Reasoning for Oil Refineries -- 7.3 Detection and Withdrawal of Defect Parts in the Computer Aided Manufacturing of Evaporators -- 7.4 Genetic Algorithms Based Fuzzy Regression Analysis and Its Applications for Quality Evaluation -- 7.5 An Intelligent System for Diagnosis of the Oil-Refinery Plant -- 7.6 Neuro-Fuzzy Pattern Recognition in Manufacturing -- 7.7 Soft Computing Based Inventory Control -- 7.8 Fuzzy Project Scheduling -- 7.9 CW Based Decision Analysis on Risk Assessment of an Engineering Project -- References -- 8 Soft Computing in Finance -- 8.1 Soft Computing Based Stock Market Predicting System -- 8.2 Fuzzy Nonlinear Programming Approach to Portfolio Selection -- 8.3 Neuro-Fuzzy Approach to Modeling of Credit Risk in Trading Portfolios -- 8.4 A Fuzzy Approach to the Credit Portfolio Constructing -- 8.5 Soft Computing Based TDSS Multi-Agent Systems in Finance -- 8.6 Neural Nonlinear Modeling for Risk Management in Banking -- 8.7 Neuro-Fuzzy Loan Assessment System -- References -- 9 Soft Computing in Electronic Business -- 9.1 A Multi-Agent System for E-Commerce Decisions -- 9.2 Soft Computing and Personalization of Electronic Commerce -- 9.3 Risk Analysis in Electronic Commerce Using Fuzzy Weighted Average -- References.