A Bee-Inspired Data Clustering Approach to Design RBF Neural Network Classifiers

Autor(es)

Ferreira Cruz, Davila Patricia ; Maia, Renato Dourado ; da Silva, Leandro Augusto ; de Castro, Leandro Nunes ; Omatu, S ; Bersini, H ; Corchado, JM ; Rodriguez, S ; Pawlewski, P ; Bucciarelli, E

• Tipo de documento: Artigo Científico
• Fonte: DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE, 11TH INTERNATIONAL CONFERENCE; v. 290, p. 8-pg., 2014-01-01.

Resumo

Different 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. (AU)

• Processo FAPESP: 13/05757-2 - Classificação de imagens combinando características visuais e dados textuais: abordagem neural e baseada em enxames
• Beneficiário: Leandro Augusto da Silva
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 13/12005-7 - Agrupamento e Classificação de Dados Usando um Algoritmo Inspirado no Comportamento de Abelhas
• Beneficiário: Dávila Patrícia Ferreira Cruz
• Modalidade de apoio: Bolsas no Brasil - Mestrado