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Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration with CDROM

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Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration with CDROM Cover

 

Synopses & Reviews

Publisher Comments:

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.

* Written to provide analysts, engineers, and managers with the background and specific instruction needed to develop and implement 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.

Synopsis:

ples in C, C++, Java, and easy-to-understand pseudo-code.

* Extensive online component, including sample code and a complete data mining workbench.

Synopsis:

menting 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.

About the Author

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.

Scianta Intelligence, LLC, Chapel Hill, NC

Table of Contents

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

Product Details

ISBN:
9780121942755
Author:
Cox, Earl
Publisher:
Morgan Kaufmann Publishers
Author:
</b><br><b>Earl Cox</b> is the founder and president of Scianta Intelligence, a next-generation machine intelligence and knowledge exploration company. He is a futurist, author, management consultant,
Subject:
Database Management - General
Subject:
Database Management - Data Warehousing and Data Mining
Subject:
Data mining
Subject:
Fuzzy logic
Subject:
Artificial Intelligence - Fuzzy Logic
Subject:
Genetic algorithms
Subject:
Database Management - Database Mining
Subject:
Artificial Intelligence
Subject:
Computer Science
Subject:
Computers-Reference - General
Series:
Morgan Kaufmann Series in Data Management Systems
Publication Date:
20050131
Binding:
TRADE PAPER
Language:
English
Illustrations:
Y
Pages:
540
Dimensions:
9.25 x 7.25 in

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Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration with CDROM New Trade Paper
0 stars - 0 reviews
$80.95 In Stock
Product details 540 pages Morgan Kaufmann Publishers - English 9780121942755 Reviews:
"Synopsis" by , ples in C, C++, Java, and easy-to-understand pseudo-code.

* Extensive online component, including sample code and a complete data mining workbench.

"Synopsis" by , menting 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.

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