Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/4643
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dc.contributor.authorAl-Enezi, JR-
dc.contributor.authorAbbod, MF-
dc.contributor.authorAlsharhan, S-
dc.date.accessioned2010-12-14T12:04:42Z-
dc.date.available2010-12-14T12:04:42Z-
dc.date.issued2010-
dc.identifier.citationInternational Journal of Research and Reviews in Applied Sciences (IJRRAS), 3(2): 118-131, May 2010en_US
dc.identifier.issn2076-734X-
dc.identifier.urihttp://www.arpapress.com/Volumes/Vol3Issue2/IJRRAS_3_2_01.pdfen
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/4643-
dc.descriptionCopyright © 2010 Academic Research Publishing Agency.en_US
dc.descriptionThis article has been made available through the Brunel Open Access Publishing Fund.-
dc.description.abstractArtificial Immune Systems (AIS) are computational paradigms that belong to the computational intelligence family and are inspired by the biological immune system. During the past decade, they have attracted a lot of interest from researchers aiming to develop immune-based models and techniques to solve complex computational or engineering problems. This work presents a survey of existing AIS models and algorithms with a focus on the last five years.en_US
dc.description.sponsorshipThis article is available through the Brunel Open Access Publishing Funden_US
dc.language.isoenen_US
dc.publisherAcademic Research Publishing Agencyen_US
dc.subjectArtificial immune systemsen_US
dc.subjectArtificial immune networksen_US
dc.subjectClonal selectionen_US
dc.subjectNegative selectionen_US
dc.titleArtificial Immune Systems - Models, algorithms and applicationsen_US
dc.typeResearch Paperen_US
Appears in Collections:Brunel OA Publishing Fund
Dept of Electronic and Electrical Engineering Research Papers

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