A fuzzy inference system to determine the number of clones in a class of artificial immune systems

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dc.contributor.authorCarraro L.A.
dc.contributor.authorDe Castro L.N.
dc.contributor.authorDe Re A.M.
dc.contributor.authorDe Frana F.O.
dc.date.accessioned2024-03-13T01:08:21Z
dc.date.available2024-03-13T01:08:21Z
dc.date.issued2012
dc.description.abstractArtificial immune systems are composed of techniques inspired by immunology. The clonal selection principle ensures the organism adaptation to fight invading antigens by an immune response activated by the binding of antigens and antibodies. Since the immune response must correctly allocate the available resources in order to attack an antigen with its best available antibody while trying to learning an even better one, the reproduction rate of each immune cell must be carefully determined. This paper presents a novel fuzzy inference technique to calculate the suitable number of clones for immune inspired algorithms that uses the clonal selection process as the evolutionary process. More specifically, this technique is applied to the CLONALG algorithm for solving pattern recognition tasks and to the copt-aiNet algorithm for solving combinatorial optimization tasks, particularly the Traveling Salesman Problem. The obtained results show that the fuzzy approach makes it possible to automatically determine the number of clones in CLONALG and copt-aiNet, thus eliminating this key user-defined parameter. © 2012 Imperial College Press.
dc.description.issuenumber1
dc.description.volume11
dc.identifier.doi10.1142/S1469026812500058
dc.identifier.issn1469-0268
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/36824
dc.relation.ispartofInternational Journal of Computational Intelligence and Applications
dc.rightsAcesso Restrito
dc.subject.otherlanguageClonal selection
dc.subject.otherlanguagefuzzy systems
dc.subject.otherlanguagepattern recognition
dc.subject.otherlanguagetraveling salesman problem
dc.titleA fuzzy inference system to determine the number of clones in a class of artificial immune systems
dc.typeArtigo
local.scopus.citations0
local.scopus.eid2-s2.0-84859762020
local.scopus.subjectArtificial Immune System
local.scopus.subjectClonal selection
local.scopus.subjectClonal selection principle
local.scopus.subjectCLONALG
local.scopus.subjectEvolutionary process
local.scopus.subjectFuzzy approach
local.scopus.subjectFuzzy inference systems
local.scopus.subjectFuzzy inference techniques
local.scopus.subjectImmune cells
local.scopus.subjectImmune response
local.scopus.subjectImmune-inspired algorithms
local.scopus.subjectUser-defined parameters
local.scopus.updated2024-05-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84859762020&origin=inward
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