Observatorio de I+D+i UPM

Memorias de investigación
Research Publications in journals:
Classification Of Data To Extract Knowledge From Neural Networks
Year:2009
Research Areas
  • Artificial intelligence
Information
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.
International
Si
JCR
No
Title
INFORMATION SCIENCE & COMPUTING
ISBN
1313-0455
Impact factor JCR
0
Impact info
Volume
Journal number
8
From page
20
To page
25
Month
ENERO
Ranking
Participants
  • Autor: Ana Martinez Blanco (UPM)
  • Autor: Angel Luis Castellanos Peñuela (UPM)
  • Autor: Rafael Gonzalo Molina (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Computación Natural
  • Departamento: Ciencias Básicas Aplicadas a la Ingeniería Forestal
  • Departamento: Inteligencia Artificial
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