Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration

Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration is a handbook for analysts, engineers, and managers. As you will discover, fuzzy systems, and the techniques of designing and tuning these systems.

You do not need a background in fuzzy modeling or genetic algorithms is a benefit, for this book it gives you the opportunity to work with your own projects. The generator provides a complex a scheduling system.

* Written to provide analysts, engineers, and more and more effective data mining systems.
* Helps you to understand the trade-offs implicit in various models and model architectures.
* Provides extensive coverage of fuzzy SQL querying, fuzzy clustering, and fuzzy rule induction.
* Lays out a roadmap for exploring data, selecting model system measures, organizing adaptive feedback loops, selecting a model configuration, implementing a working model, and validating the final model.
* In an extended example, applies evolutionary programming techniques to solve a complicated scheduling problem.
* Presents examples in C, C ++, Java, and easy-to-understand pseudo-code.
* Extensive online component, including sample code and a complete data mining workbench.

Preface
acknowledgments
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