A bee-inspired data clustering approach to design RBF neural network classifiers

dc.contributor.authorCruz D.P.F.
dc.contributor.authorda Silva L.A.
dc.contributor.authorde Castro L.N.
dc.contributor.authorMaia R.D.
dc.date.accessioned2024-03-13T01:01:59Z
dc.date.available2024-03-13T01:01:59Z
dc.date.issued2014
dc.description.abstractDifferent methods have been used to train radial basis function neural networks. This paper proposes a bee-inspired algorithm to automatically select the number and location of basis functions to be used in such RBF network. The algorithm was designed to solve data clustering problems, where the centroids of clusters are used as centers for the RBF network. The approach presented in this paper is preliminary evaluated in three synthetic datasets, two classification datasets and one function approximation problem, and its results suggest a potential for real-world application. © Springer International Publishing Switzerland 2014.
dc.description.firstpage545
dc.description.lastpage552
dc.description.volume290
dc.identifier.doi10.1007/978-3-319-07593-8_63
dc.identifier.issn2194-5357
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/36465
dc.relation.ispartofAdvances in Intelligent Systems and Computing
dc.rightsAcesso Restrito
dc.subject.otherlanguageBee-inspired algorithms
dc.subject.otherlanguageNeural network
dc.subject.otherlanguageOptimal data clustering
dc.subject.otherlanguageRBF
dc.titleA bee-inspired data clustering approach to design RBF neural network classifiers
dc.typeArtigo de evento
local.scopus.citations3
local.scopus.eid2-s2.0-84906050621
local.scopus.subjectBee-inspired algorithms
local.scopus.subjectClassification datasets
local.scopus.subjectFunction approximation problems
local.scopus.subjectOptimal data
local.scopus.subjectRadial basis function neural networks
local.scopus.subjectRBF
local.scopus.subjectRBF Neural Network
local.scopus.subjectSynthetic datasets
local.scopus.updated2024-05-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84906050621&origin=inward
Arquivos