Fuzzy modeling and genetic algorithms for data mining and exploration
著者
書誌事項
Fuzzy modeling and genetic algorithms for data mining and exploration
（The Morgan Kaufmann series in data management systems）
Morgan Kaufmann, c2005
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration is a handbook for analysts, engineers, and managers involved in developing data mining models in business and government. As you'll discover, fuzzy systems are extraordinarily valuable tools for representing and manipulating all kinds of data, and genetic algorithms and evolutionary programming techniques drawn from biology provide the most effective means for designing and tuning these systems.
You don't need a background in fuzzy modeling or genetic algorithms to benefit, for this book provides it, along with detailed instruction in methods that you can immediately put to work in your own projects. The author provides many diverse examples and also an extended example in which evolutionary strategies are used to create a complex scheduling system.
目次
Preface
Acknowledgements
Introduction
PART ONE - CONCEPTS AND ISSUES
Chapter 1. Foundations and Ideas
Chapter 2. Principal Model Types
Chapter 3. Approaches to Model Building
PART TWO - FUZZY SYSTEMS
Chapter 4. Fundamental Concepts of Fuzzy Logic
Chapter 5. Fundamental Concepts of Fuzzy Systems
Chapter 6. FuzzySQL and Intelligent Queries
Chapter 7. Fuzzy Clustering
Chapter 8. Fuzzy Rule Induction
PART THREE - EVOLUTIONARY STRATEGIES
Chapter 9. Fundamental Concepts of Genetic Algorithms
Chapter 10. Genetic Resource Scheduling Optimization
Chapter 11. Genetic Tuning of Fuzzy Models
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