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Descripción
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| Abstract: A major drawback of artificial neural networks is their black-box character. Therefore, the rule extraction algorithm is becoming more and more important in explaining the extracted rules from the neural networks. In this paper, we use a method that can be used for symbolic knowledge extraction from neural networks, once they have been trained with desired function. The basis of this method is the weights of the neural network trained. This method allows knowledge extraction from neural networks with continuous inputs and output as well as rule extraction. An example of the application is showed. This example is based on the extraction of average load demand of a power plant. | |
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Internacional
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Si |
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Nombre congreso
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"Information Research and Applications" (i.TECH 2009) |
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Tipo de participación
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960 |
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Lugar del congreso
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Varna Bulgaria |
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Revisores
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Si |
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ISBN o ISSN
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1313-0455 |
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DOI
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Fecha inicio congreso
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24/06/2009 |
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Fecha fin congreso
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02/07/2009 |
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Desde la página
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20 |
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Hasta la página
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27 |
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Título de las actas
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International Book Series "INFORMATION SCIENCE & COMPUTING", Number 8 Supplement to the International Journal "INFORMATION TECHNOLOGIES & KNOWLEDGE" Volume 3, 2009 |