Business Applications and Computational Intelligence

Description

Computational intelligence has a long history of applications to business - expert systems have been used for decision support in management, neural networks and fuzzy logic have been used in process control, a variety of techniques have been used in forecasting and data mining has become a core component of customer relationship management in marketing. While there is literature on this field, it is spread over many disciplines and in many different publications, making it difficult to find the pertinent information in one source. Business Applications and Computational Intelligence addresses the need for a compact overview of the diversity of applications in a number of business disciplines, and consists of chapters written by leading international researchers. Chapters cover most fields of business, including: marketing, data mining, e-commerce, production and operations, finance, decision-making, and general management. Business Applications and Computational Intelligence provides a comprehensive review of research into computational intelligence applications in business, creating a powerful guide for both newcomers and experienced researchers. Title Page Copyright Page Table of Contents Preface Acknowledgments Section 1: Introduction Chapter 1: Computational Intelligence Applications in Business Chapter 2: Making Decisions with Data Chapter 3: Computational Intelligence as a Platform for a Data Collection Methodology in Management Science Section 2: Marketing Applications Chapter 4: Heuristic Genetic Algorithm for Product Portfolio Planning Chapter 5: Modeling Brand Choice Using Boosted and Stacked Neural Networks Chapter 6: Applying Information Gathering Techniques in Business-to-Consumer and Web Scenarios Chapter 7: Web Mining System for Mobile-Phone Marketing Section 3: Production and Operations Applications Chapter 8: Artificial Intelligence in Electricity Market Operations and Management Chapter 9: Reinforcement Learning-Based Intelligent Agents for Improved Productivity in Container Vessel Berthing Applications Chapter 10: Optimization Using Horizon-Scan Technique Section 4: Data Mining Applications Chapter 11: Visual Data Mining for Discovering Association Rules Chapter 12: Analytical Customer Requirement Analysis Based on Data Mining Chapter 13: Visual Grouping of Association Rules by Clustering Conditional Probabilities for Categorical Data Chapter 14: Support Vector Machines for Business Applications Chapter 15: Algorithms for Data Mining Section 5: Management Applications Chapter 16: A Tool for Assisting Group Decision-Making for Consensus Outcomes in Organizations Chapter 17: Analyzing Strategic Stance in Public Services Management Chapter 18: The Analytic Network Process – Dependence and Feedback in Decision-Making Section 6: Financial Applications Chapter 19: Financial Classification Using an Artificial Immune System Chapter 20: Development of Machine Learning Software for High Frequency Trading in Financial Markets Chapter 21: Online Methods for Portfolio Selection Section 7: Postscript Chapter 22: Ankle Bones, Rogues, and Sexual Freedom for Women About the Authors Index