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Registros recuperados : 96 | |
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Registro Completo
Biblioteca(s): |
Embrapa Cerrados. |
Data corrente: |
29/08/2002 |
Data da última atualização: |
29/08/2002 |
Autoria: |
PRADO, H. A.; FRIGERI, S. R.; ENGEL, P. M. |
Título: |
A parsimonious generation of combinatorial neural model. |
Ano de publicação: |
1998 |
Fonte/Imprenta: |
In: CACIC. Neuquen, Argentina: Universidade Nacional del Comahue, 1998. |
Idioma: |
Inglês |
Conteúdo: |
This paper a new approach to reduce the space problem due to combinatorial explosion of CNM (Combinatorial Neural Model) method. First we show a description of CNM, proposed by Machado and Rocha [MAC 91], [MAC 92], [MAC 92a], [MAC 97], as a variation of fuzzy neural network introduced as an alternative to meet many requirements, such as expressivenes, inteligibility, plasticity and flexibility. Our approach represents an alternative to generate the CNM network with certainty factors for each hypothesis. We demonstrate by means of a simple practical example that the number of combinations can be really reduced. |
Palavras-Chave: |
Data mining; Knowledge discovery; Redes neurais. |
Thesagro: |
Base de Dados; Informática. |
Thesaurus NAL: |
databases; neural networks. |
Categoria do assunto: |
-- |
Marc: |
LEADER 01238naa a2200229 a 4500 001 1565253 005 2002-08-29 008 1998 bl uuuu u00u1 u #d 100 1 $aPRADO, H. A. 245 $aA parsimonious generation of combinatorial neural model. 260 $c1998 520 $aThis paper a new approach to reduce the space problem due to combinatorial explosion of CNM (Combinatorial Neural Model) method. First we show a description of CNM, proposed by Machado and Rocha [MAC 91], [MAC 92], [MAC 92a], [MAC 97], as a variation of fuzzy neural network introduced as an alternative to meet many requirements, such as expressivenes, inteligibility, plasticity and flexibility. Our approach represents an alternative to generate the CNM network with certainty factors for each hypothesis. We demonstrate by means of a simple practical example that the number of combinations can be really reduced. 650 $adatabases 650 $aneural networks 650 $aBase de Dados 650 $aInformática 653 $aData mining 653 $aKnowledge discovery 653 $aRedes neurais 700 1 $aFRIGERI, S. R. 700 1 $aENGEL, P. M. 773 $tIn: CACIC. Neuquen, Argentina: Universidade Nacional del Comahue, 1998.
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