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Artificial immune system based on hybrid and external memory for mathematical function optimization

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dc.citedby2
dc.contributor.authorYap D.F.W.en_US
dc.contributor.authorKoh S.P.en_US
dc.contributor.authorTiong S.K.en_US
dc.contributor.authorid22952562500en_US
dc.contributor.authorid22951210700en_US
dc.contributor.authorid15128307800en_US
dc.date.accessioned2023-12-28T07:05:43Z
dc.date.available2023-12-28T07:05:43Z
dc.date.issued2011
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 further improved 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. Thus, a hybrid PSO-AIS and a new external memory CSA based scheme called EMCSA are proposed. In hybrid PSO-AIS, the good features of PSO and AIS are combined in order to reduce any limitation. Alternatively, EMCSA captures all the best antibodies into the memory in order to enhance global searching capability. In this preliminary study, the results show that the performance of hybrid PSO-AIS compares favourably with other algorithms while EMCSA produced moderate results in most of the simulations. � 2011 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo5958875
dc.identifier.doi10.1109/ISCI.2011.5958875
dc.identifier.epage17
dc.identifier.scopus2-s2.0-80052129975
dc.identifier.spage12
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-80052129975&doi=10.1109%2fISCI.2011.5958875&partnerID=40&md5=d20187d0ef90ee6da216bf3a38f3349e
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/29586
dc.pagecount5
dc.sourceScopus
dc.sourcetitleISCI 2011 - 2011 IEEE Symposium on Computers and Informatics
dc.subjectaffinity maturation
dc.subjectantibody
dc.subjectantigen
dc.subjectclonal selection
dc.subjectmutation
dc.subjectAlgorithms
dc.subjectAntibodies
dc.subjectFunctions
dc.subjectImmunology
dc.subjectInformation science
dc.subjectAffinity maturation
dc.subjectArtificial Immune System
dc.subjectClonal selection
dc.subjectClonal selection algorithms
dc.subjectComplex optimization
dc.subjectExternal memory
dc.subjectGlobal searching ability
dc.subjectGlobal searching capabilities
dc.subjectHyper mutation
dc.subjectMathematical functions
dc.subjectmutation
dc.subjectNature-inspired algorithms
dc.subjectOptimization problems
dc.subjectOther algorithms
dc.subjectParticle swarm optimization (PSO)
dc.titleArtificial immune system based on hybrid and external memory for mathematical function optimizationen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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