Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/104159
Type: Artigo de evento
Title: Training Neurofuzzy Networks With Participatory Learning
Author: Hell M.
Ballini R.
Costa P.
Gomide F.
Abstract: This paper introduces a new approach to adjust a class of neurofuzzy networks based on the idea of participatory learning. Participatory learning is a mean to learn and revise beliefs based on what is already known or believed. The performance of the approach is verified with the Box and Jenkins gas furnace modeling problem, and with a shortterm load forecasting problem using actual data. Comparisons with alternative training procedures suggested in the literature are included to shown the effectiveness of participatory learning to train neurofuzzy networks.
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Rights: fechado
Identifier DOI: 
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-80053575573&partnerID=40&md5=93a6d358b7dfd56ed3edebb1a9fb8b92
Date Issue: 2007
Appears in Collections:Unicamp - Artigos e Outros Documentos

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