Show simple item record

dc.contributor.editorLazinica, Aleksandar
dc.date.accessioned2021-04-20T14:54:07Z
dc.date.available2021-04-20T14:54:07Z
dc.date.issued2009
dc.identifierONIX_20210420_9789537619480_76
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/64720
dc.description.abstractParticle swarm optimization (PSO) is a population based stochastic optimization technique influenced by the social behavior of bird flocking or fish schooling.PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UY Computer science::UYF Computer architecture and logic designen_US
dc.subject.otherComputer architecture & logic design
dc.titleParticle Swarm Optimization
dc.typebook
oapen.identifier.doi10.5772/109
oapen.relation.isPublishedBy78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6
oapen.relation.isbn9789537619480
oapen.relation.isbn9789535157472
oapen.imprintIntechOpen
oapen.pages488


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record

https://creativecommons.org/licenses/by-nc-sa/3.0/
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by-nc-sa/3.0/