
Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration
Earl Cox(Author)
Morgan Kaufmann (Publisher)
Published on 24. February 2005
Book
Paperback/Softback
540 pages
978-0-12-194275-5 (ISBN)
Description
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.
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.
More details
Series
Language
English
Place of publication
San Francisco
United States
Publishing group
Elsevier Science & Technology
Target group
Professional and scholarly
Researchers and technicians in organisations with large databases.
Dimensions
Height: 259 mm
Width: 184 mm
Weight
1110 gr
ISBN-13
978-0-12-194275-5 (9780121942755)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

E-Book
02/2005
Morgan Kaufmann
€53.95
Available for download
Person
Earl founded and serves as President of, Scianta Intelligence, a next generation machine intelligence and knowledge exploration company. He is a futurist, author, management consultant, and educator involved in discovering the epistemology of advanced intelligent systems, the redefinition of the machine mind, and, as a pioneer of Internet-based technologies, the way in which evolving inter-connected virtual worlds will affect the sociology of business and culture in the near and far future.Earl has over thirty years experience in managing and participating in the software development process at the system as well as tightly integrated application level. In the area of advanced machine intelligence technologies, Earl is a recognized expert in fuzzy logic, and adaptive fuzzy systems as they are applied to information and decision theory. He has pioneered the integration of fuzzy neural systems with genetic algorithms and case-based reasoning. As an industry observer and futurist, Earl has written and talked extensively on the philosophy of the Response to Change, the nature of Emergent Intelligence, and the Meaning of Information Entropy in Mind and Machine.
Content
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
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