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Fuzzy modeling and genetic algorithm...

Cox, Earl.

Fuzzy modeling and genetic algorithms for data mining and exploration

Record Type:	Electronic resources : Monograph/item
Title/Author:	Fuzzy modeling and genetic algorithms for data mining and explorationEarl Cox.
Author:	Cox, Earl.
Published:	Amsterdam ;Elsevier/Morgan Kaufmann,c2005.
Description:	xxi, 530 p. :ill. ;24 cm.
Series:	The Morgan Kaufmann series in data management systems
Subject:	Data mining.
Online resource:	An electronic book accessible through the World Wide Web; click for information
Online resource:	http://www.engineeringvillage.com/controller/servlet/OpenURL?genre=book&isbn=9780121942755
Online resource:	http://www.loc.gov/catdir/enhancements/fy0619/2004061901-d.html
Online resource:	http://www.loc.gov/catdir/enhancements/fy0619/2004061901-t.html
ISBN:	9780121942755

Fuzzy modeling and genetic algorithms for data mining and exploration
Cox, Earl.

Fuzzy modeling and genetic algorithms for data mining and exploration[electronic resource] /Earl Cox. - Amsterdam ;Elsevier/Morgan Kaufmann,c2005. - xxi, 530 p. :ill. ;24 cm. - The Morgan Kaufmann series in data management systems.

Includes bibliographical references and index.

Foundations and ideas -- Principal model types -- Approaches to model building -- Fundamental concepts of fuzzy logic -- Fundamental concepts of fuzzy systems -- Fuzzy SQL and intelligent queries -- Fuzzy clustering -- Fuzzy rule induction -- Fundamental concepts of genetic algorithms -- Genetic resource scheduling optimization -- Genetic tuning of fuzzy models.

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 youll 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 dont 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.

Electronic reproduction.
Amsterdam :
Elsevier Science & Technology,
2007.

Mode of access: World Wide Web.

ISBN: 9780121942755

Source: 88646:88646Elsevier Science & Technologyhttp://www.sciencedirect.comSubjects--Topical Terms:

184440
Data mining.
Index Terms--Genre/Form:

214472
Electronic books.

LC Class. No.: QA9.64 / .C69 2005eb

Dewey Class. No.: 006.3/12

Fuzzy modeling and genetic algorithms for data mining and exploration
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245 1 0 $a Fuzzy modeling and genetic algorithms for data mining and exploration $h [electronic resource] / $c Earl Cox.
260 $a Amsterdam ; $a Boston : $c c2005. $b Elsevier/Morgan Kaufmann,
300 $a xxi, 530 p. : $b ill. ; $c 24 cm.
440 4 $a The Morgan Kaufmann series in data management systems
504 $a Includes bibliographical references and index.
505 0 $a Foundations and ideas -- Principal model types -- Approaches to model building -- Fundamental concepts of fuzzy logic -- Fundamental concepts of fuzzy systems -- Fuzzy SQL and intelligent queries -- Fuzzy clustering -- Fuzzy rule induction -- Fundamental concepts of genetic algorithms -- Genetic resource scheduling optimization -- Genetic tuning of fuzzy models.
520 $a 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 youll 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 dont 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.
533 $a Electronic reproduction. $b Amsterdam : $c Elsevier Science & Technology, $d 2007. $n Mode of access: World Wide Web. $n System requirements: Web browser. $n Title from title screen (viewed on Aug. 2, 2007). $n Access may be restricted to users at subscribing institutions.
650 0 $a Data mining. $3 184440
650 0 $a Fuzzy logic. $3 181981
650 0 $a Genetic algorithms. $3 182939
650 1 7 $a Genetische algoritmen. $2 gtt $3 340583
655 7 $a Electronic books. $2 local. $3 214472
710 2 $a ScienceDirect (Online service) $3 307425
856 4 0 $3 ScienceDirect $u http://www.sciencedirect.com/science/book/9780121942755 $z An electronic book accessible through the World Wide Web; click for information
856 4 0 $3 Referex $u http://www.engineeringvillage.com/controller/servlet/OpenURL?genre=book&isbn=9780121942755 $z An electronic book accessible through the World Wide Web; click for information
856 4 2 $3 Publisher description $u http://www.loc.gov/catdir/enhancements/fy0619/2004061901-d.html
856 4 1 $3 Table of contents only $u http://www.loc.gov/catdir/enhancements/fy0619/2004061901-t.html
994 $a C0 $b TEF

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http://www.loc.gov/catdir/enhancements/fy0619/2004061901-t.html

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