Knowledge incorporation and rule extraction in neural networks

Minoru Fukumi, Yasue Mitsukura, Norio Akamatsu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper a new knowledge incorporation and rule extraction method in neural networks is presented. The rule form of an if–then type can be inserted into a neural network (NN) as knowledge of a problem. NN is then trained by using a set of training samples. In this case the structure learning algorithm with forgetting is used to generate a small-sized NN system. After the NN training, rules are extracted from it. The results of computer simulations show that this approach can generate obvious network architectures and as a result simple rules compared with conventional rule extraction methods.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages1248-1253
Number of pages6
Volume2130
ISBN (Print)3540424865, 9783540446682
DOIs
Publication statusPublished - 2001
Externally publishedYes
EventInternational Conference on Artificial Neural Networks, ICANN 2001 - Vienna, Austria
Duration: 2001 Aug 212001 Aug 25

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2130
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

OtherInternational Conference on Artificial Neural Networks, ICANN 2001
CountryAustria
CityVienna
Period01/8/2101/8/25

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ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Fukumi, M., Mitsukura, Y., & Akamatsu, N. (2001). Knowledge incorporation and rule extraction in neural networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2130, pp. 1248-1253). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2130). Springer Verlag. https://doi.org/10.1007/3-540-44668-0_174