Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/93357
Type: Artigo de evento
Title: Data Clustering With A Neuro-immune Network
Author: Knidel H.
De Castro L.N.
Von Zuben F.J.
Abstract: This paper proposes a novel constructive learning algorithm for a competitive neural network. The proposed algorithm is developed by taking ideas from the immune system and demonstrates robustness for data clustering in the initial experiments reported here for three benchmark problems. Comparisons with results from the literature are also provided. To automatically segment the resultant neurons at the output, a tool from graph theory was used with promising results. A brief sensitivity analysis of the algorithm was performed in order to investigate the influence of the main user-defined parameters on the learning speed and accuracy of the results presented. General discussions and avenues for future works are also provided. © Springer-Verlag Berlin Heidelberg 2005.
Editor: 
Rights: fechado
Identifier DOI: 
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-26844434710&partnerID=40&md5=bcc7a99488a49c4f01c5ca34a0566886
Date Issue: 2005
Appears in Collections:Unicamp - Artigos e Outros Documentos

Files in This Item:
File Description SizeFormat 
2-s2.0-26844434710.pdf235.58 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.