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Solving computational algorithm using CLONALNet technique based on artificial clonal selection

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dc.citedby0
dc.contributor.authorSamy J.A.L.A.en_US
dc.contributor.authorKrishnan P.S.A.L.en_US
dc.contributor.authorKiong T.S.en_US
dc.contributor.authorid54584226700en_US
dc.contributor.authorid36053261400en_US
dc.contributor.authorid15128307800en_US
dc.date.accessioned2023-12-29T07:48:26Z
dc.date.available2023-12-29T07:48:26Z
dc.date.issued2011
dc.description.abstractThis paper discusses the approach of CLONALNet in determining the optimum fitness function and mean population by benchmarking it with CLONALG. By using this algorithm the steps to obtain the fitness function is optimized and processing time is reduced. CLONALNet is a hybrid or combination of both opt-aiNet (Optimize Artificial Immune Network) and CLONALG. CLONALNet enforces an algorithm that is much more robust in evaluating the fitness for each antibody cells since it initiates boundaries so that the initialization process doesn't run off as of previous CLONALG algorithm but still maintains the immune network interaction as in aiNet. Also included is the combination of steps which includes cloning, affinity maturation and selection steps into one single function to find the best group of clones. In recent studies done, the maximum value will be the optimum solution. The optimum result as suggested in this paper is the minimum value for fitness function referring to global optimum result which is zero. � 2011 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo6079255
dc.identifier.doi10.1109/ICOS.2011.6079255
dc.identifier.epage347
dc.identifier.scopus2-s2.0-83155178468
dc.identifier.spage344
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-83155178468&doi=10.1109%2fICOS.2011.6079255&partnerID=40&md5=7d47b796576bcf758f846241bed4c243
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/30491
dc.pagecount3
dc.publisherIEEE Computer Societyen_US
dc.sourceScopus
dc.sourcetitle2011 IEEE Conference on Open Systems, ICOS 2011
dc.subjectCLONALNet
dc.subjectdata acquisition
dc.subjectGaussian
dc.subjectMultifunction
dc.subjectmutation rate
dc.subjectClone cells
dc.subjectCloning
dc.subjectData acquisition
dc.subjectAffinity maturation
dc.subjectArtificial immune networks
dc.subjectCLONALNet
dc.subjectComputational algorithm
dc.subjectFitness functions
dc.subjectGaussians
dc.subjectMultifunction
dc.subjectMutation rates
dc.subjectHealth
dc.titleSolving computational algorithm using CLONALNet technique based on artificial clonal selectionen_US
dc.typeConference paperen_US
dspace.entity.typePublication
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