Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases (Hardcover, 2008 ed.)


The present volume provides a collection of seven articles containing new and high quality research results demonstrating the significance of Multi-objective Evolutionary Algorithms (MOEA) for data mining tasks in Knowledge Discovery from Databases (KDD). These articles are written by leading experts around the world. It is shown how the different MOEAs can be utilized, both in individual and integrated manner, in various ways to efficiently mine data from large databases.


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Product Description

The present volume provides a collection of seven articles containing new and high quality research results demonstrating the significance of Multi-objective Evolutionary Algorithms (MOEA) for data mining tasks in Knowledge Discovery from Databases (KDD). These articles are written by leading experts around the world. It is shown how the different MOEAs can be utilized, both in individual and integrated manner, in various ways to efficiently mine data from large databases.

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Product Details

General

Imprint

Springer-Verlag

Country of origin

Germany

Series

Studies in Computational Intelligence, 98

Release date

March 2008

Availability

Expected to ship within 10 - 15 working days

First published

May 2008

Editors

, ,

Dimensions

235 x 155 x 11mm (L x W x T)

Format

Hardcover

Pages

162

Edition

2008 ed.

ISBN-13

978-3-540-77466-2

Barcode

9783540774662

Categories

LSN

3-540-77466-1



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