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Swarm Intelligence for Multi-objective Problems in Data Mining (Hardcover, 2010 ed.) Loot Price: R4,400
Discovery Miles 44 000
Swarm Intelligence for Multi-objective Problems in Data Mining (Hardcover, 2010 ed.): Carlos Coello Coello, Satchidananda...

Swarm Intelligence for Multi-objective Problems in Data Mining (Hardcover, 2010 ed.)

Carlos Coello Coello, Satchidananda Dehuri, Susmita Ghosh

Series: Studies in Computational Intelligence, 242

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Loot Price R4,400 Discovery Miles 44 000 | Repayment Terms: R412 pm x 12*

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Multi-objective optimization deals with the simultaneous optimization of two or more objectives which are normally in con?ict with each other. Since mul- objective optimization problems are relatively common in real-world appli- tions, this area has become a very popular research topic since the 1970s. However, the use of bio-inspired metaheuristics for solving multi-objective op- mization problems started in the mid-1980s and became popular until the mid- 1990s. Nevertheless, the e?ectiveness of multi-objective evolutionary algorithms has made them very popular in a variety of domains. Swarm intelligence refers to certain population-based metaheuristics that are inspired on the behavior of groups of entities (i.e., living beings) interacting locallywitheachotherandwiththeirenvironment.Suchinteractionsproducean emergentbehaviorthatismodelledinacomputerinordertosolveproblems.The two most popular metaheuristics within swarm intelligence are particle swarm optimization (which simulates a ?ock of birds seeking food) and ant colony optimization (which simulates the behavior of colonies of real ants that leave their nest looking for food). These two metaheuristics havebecome verypopular inthelastfewyears, andhavebeenwidelyusedinavarietyofoptimizationtasks, including some related to data mining and knowledge discovery in databases. However, such work has been mainly focused on single-objective optimization models. The use of multi-objective extensions of swarm intelligence techniques in data mining has been relatively scarce, in spite of their great potential, which constituted the main motivation to produce this book

General

Imprint: Springer-Verlag
Country of origin: Germany
Series: Studies in Computational Intelligence, 242
Release date: September 2009
First published: 2010
Editors: Carlos Coello Coello • Satchidananda Dehuri • Susmita Ghosh
Dimensions: 235 x 155 x 17mm (L x W x T)
Format: Hardcover
Pages: 287
Edition: 2010 ed.
ISBN-13: 978-3-642-03624-8
Categories: Books > Professional & Technical > Technology: general issues > Technical design > Computer aided design (CAD)
Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN: 3-642-03624-4
Barcode: 9783642036248

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