Multiobjective Genetic Algorithms for Clustering : Applications in Data Mining and Bioinformatics

Ujjwal Maulik

ISBN 10: 3642166148 / ISBN 13: 9783642166143

Published by Springer Berlin Heidelberg, 2011

About this Item

Druck auf Anfrage Neuware - Printed after ordering - This is the first book primarily dedicated to clustering using multiobjective genetic algorithms with extensive real-life applications in data mining and bioinformatics. The authors first offer detailed introductions to the relevant techniques - genetic algorithms, multiobjective optimization, soft computing, data mining and bioinformatics. They then demonstrate systematic applications of these techniques to real-world problems in the areas of data mining, bioinformatics and geoscience. The authors offer detailed theoretical and statistical notes, guides to future research, and chapter summaries.The book can be used as a textbook and as a reference book by graduate students and academic and industrial researchers in the areas of soft computing, data mining, bioinformatics and geoscience.

Seller Inventory # 9783642166143

Bibliographic Details

• Title: Multiobjective Genetic Algorithms for Clustering : Applications in Data Mining and Bioinformatics
• Publisher: Springer Berlin Heidelberg
• Publication Date: 2011
• Language: English
• ISBN 10: 3642166148
• ISBN 13: 9783642166143
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 21D millimeters 241 millimeters width by 160 millimeters height by 21 millimeters depth
• Weight: 617 grams

About this title

Synopsis

This is the first book primarily dedicated to clustering using multiobjective genetic algorithms with extensive real-life applications in data mining and bioinformatics. The authors first offer detailed introductions to the relevant techniques – genetic algorithms, multiobjective optimization, soft computing, data mining and bioinformatics. They then demonstrate systematic applications of these techniques to real-world problems in the areas of data mining, bioinformatics and geoscience. The authors offer detailed theoretical and statistical notes, guides to future research, and chapter summaries.

The book can be used as a textbook and as a reference book by graduate students and academic and industrial researchers in the areas of soft computing, data mining, bioinformatics and geoscience.