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An improved artificial immune system based on antibody remainder method for mathematical function optimization

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dc.citedby2
dc.contributor.authorYap D.F.W.en_US
dc.contributor.authorHabibullah A.en_US
dc.contributor.authorKoh S.P.en_US
dc.contributor.authorTiong S.K.en_US
dc.contributor.authorid22952562500en_US
dc.contributor.authorid58205905000en_US
dc.contributor.authorid22951210700en_US
dc.contributor.authorid15128307800en_US
dc.date.accessioned2023-12-28T07:17:47Z
dc.date.available2023-12-28T07:17:47Z
dc.date.issued2010
dc.description.abstractArtificial immune system (AIS) is one of the nature-inspired algorithm for optimization problem. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability. However, the CSA convergence and accuracy can be improved further because the hypermutation in CSA itself cannot always guarantee a better solution. Alternatively, Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) have been used efficiently in solving complex optimization problems, but they have a tendency to converge prematurely. In this study, the CSA is modified using the best solutions for each exposure (iteration) namely Remainder-CSA. The results show that the proposed algorithm is able to improve the conventional CSA in terms of accuracy and stability for single objective functions. �2010 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo5703996
dc.identifier.doi10.1109/SCORED.2010.5703996
dc.identifier.epage177
dc.identifier.scopus2-s2.0-79951963966
dc.identifier.spage174
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-79951963966&doi=10.1109%2fSCORED.2010.5703996&partnerID=40&md5=dbb3cca29c289f724c6042229fd41c6c
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/29626
dc.pagecount3
dc.sourceScopus
dc.sourcetitleProceeding, 2010 IEEE Student Conference on Research and Development - Engineering: Innovation and Beyond, SCOReD 2010
dc.subjectAffinity maturation
dc.subjectAntibody
dc.subjectAntigen
dc.subjectClonal selection
dc.subjectComponent
dc.subjectMutation
dc.subjectAlgorithms
dc.subjectAntibodies
dc.subjectAntigens
dc.subjectEngineering research
dc.subjectFunctions
dc.subjectImmunology
dc.subjectInnovation
dc.subjectAffinity maturation
dc.subjectArtificial Immune System
dc.subjectClonal selection
dc.subjectClonal selection algorithms
dc.subjectComplex optimization
dc.subjectComponent
dc.subjectGlobal searching ability
dc.subjectHyper mutation
dc.subjectMathematical functions
dc.subjectMutation
dc.subjectNature-inspired algorithms
dc.subjectOptimization problems
dc.subjectSingle objective
dc.subjectParticle swarm optimization (PSO)
dc.titleAn improved artificial immune system based on antibody remainder method for mathematical function optimizationen_US
dc.typeConference paperen_US
dspace.entity.typePublication
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