Descripción
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Social behavior is mainly based on swarm colonies, in which each individual shares its knowledge about the environment with other individuals to get optimal solutions. Such co-operative model differs from competitive models in the way that individuals die and are born by combining information of alive ones. This paper presents the particle swarm optimization with differential evolution algorithm in order to train a neural network instead the classic back propagation algorithm. The performance of a neural network for particular problems is critically dependant on the choice of the processing elements, the net architecture and the learning algorithm. This work is focused in the development of methods for the evolutionary design of artificial neural networks. This paper focuses in optimizing the topology and structure of connectivity for these networks | |
Internacional
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JCR del ISI
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Si |
Título de la revista
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International Journal Information Content and Processing |
ISSN
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2367-5128 |
Factor de impacto JCR
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Información de impacto
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Volumen
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1 |
DOI
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Número de revista
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2 |
Desde la página
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103 |
Hasta la página
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114 |
Mes
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SIN MES |
Ranking
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