A fuzzy inference system to determine the number of clones in the clonal selection algorithm

Página do item simplificado
dc.contributor.authorCarraro L.A.
dc.contributor.authorDe Castro L.N.
dc.contributor.authorDe Re A.M.
dc.date.accessioned2024-03-13T01:30:22Z
dc.date.available2024-03-13T01:30:22Z
dc.date.issued2010
dc.description.abstractArtificial Immune Systems (AISs) 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. As an immune response can be elicited even when the binding between an antigen and an antibody is not perfect, an approximate binding might suffice, and a Fuzzy Logic mechanism might be the most appropriate mechanism to control such process. This paper presents a novel hybrid model based on concepts of Immune and Fuzzy Systems with applications to pattern recognition problems. The preliminary results obtained here suggest the proposed model is a promising pattern recognition tool. © 2010 IEEE.
dc.description.firstpage98
dc.description.lastpage102
dc.identifier.doi10.1109/NABIC.2010.5716299
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/37120
dc.relation.ispartofProceedings - 2010 2nd World Congress on Nature and Biologically Inspired Computing, NaBIC 2010
dc.rightsAcesso Restrito
dc.subject.otherlanguageClonal selection
dc.subject.otherlanguageFuzzy systems
dc.subject.otherlanguagePattern recognition
dc.titleA fuzzy inference system to determine the number of clones in the clonal selection algorithm
dc.typeArtigo de evento
local.scopus.citations0
local.scopus.eid2-s2.0-79952745241
local.scopus.subjectArtificial Immune System
local.scopus.subjectClonal selection
local.scopus.subjectClonal selection algorithms
local.scopus.subjectClonal selection principle
local.scopus.subjectFuzzy inference systems
local.scopus.subjectHybrid model
local.scopus.subjectImmune response
local.scopus.subjectPattern recognition problems
local.scopus.updated2024-05-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79952745241&origin=inward
Arquivos
Coleções
Artigo de evento