An "Artificial Expert"-Knowledge Acquisition via Neural Networks
Zhe , Ma. and Harrison, R.F.
(1995)
An "Artificial Expert"-Knowledge Acquisition via Neural Networks.
Research Report.
ACSE Research Report 578
.
Department of Automatic Control and Systems Engineering
Abstract
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.
Metadata
Item Type:
Monograph
Authors/Creators:
Zhe , Ma.
Harrison, R.F.
Copyright, Publisher and Additional Information:
The Department of Automatic Control and Systems Engineering research reports offer a forum for the research output of the academic staff and research students of the Department at the University of Sheffield. Papers are reviewed for quality and presentation by a departmental editor. However, the contents and opinions expressed remain the responsibility of the authors. Some papers in the series may have been subsequently published elsewhere and you are advised to cite the later published version in these instances.
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