@inproceedings{c8ed669d24a34dfd917a52c80b823101,
title = "Knowledge incorporation and rule extraction in neural networks",
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.",
author = "Minoru Fukumi and Yasue Mitsukura and Norio Akamatsu",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2001.; International Conference on Artificial Neural Networks, ICANN 2001 ; Conference date: 21-08-2001 Through 25-08-2001",
year = "2001",
doi = "10.1007/3-540-44668-0_174",
language = "English",
isbn = "3540424865",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "1248--1253",
editor = "Kurt Hornik and Georg Dorffner and Horst Bischof",
booktitle = "Artificial Neural Networks - ICANN 2001 - International Conference, Proceedings",
}