An "Artificial Expert"-Knowledge Acquisition via Neural Networks

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Zhe , Ma. ; Harrison, R.F. (1995)
  • Publisher: Department of Automatic Control and Systems Engineering
  • Subject:
    arxiv: Computer Science::Neural and Evolutionary Computation

Artificial neural networks (ANN's) perform adaptive learning. This advantage can be used to solve knowledge acquisition bottle-neck in knowledge engineering by rule extraction from the ANN's. This paper proposes a rule extraction method combining both open-box (white-box) and black-box approaches to analyse a trained Multilayer Perceptron in order to extract general production rules accurately, abstractly and efficiently.
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