@misc{10481/77893,
year = {2006},
month = {5},
url = {https://hdl.handle.net/10481/77893},
abstract = {A method to extract a fuzzy rule based system from a trained artificial neural network for classification
is presented. The fuzzy system obtained is equivalent to the corresponding neural network.
In the antecedents of the fuzzy rules, it uses the similarity between the input datum and the weight
vectors. This implies rules highly understandable. Thus, both the fuzzy system and a simple analysis
of the weight vectors are enough to discern the hidden knowledge learnt by the neural network. Several
classification problems are presented to illustrate this method of knowledge discovery by using
artificial neural networks.},
publisher = {Elsevier},
keywords = {Artificial neural networks},
keywords = {Fuzzy systems},
keywords = {Inteligencia artificial},
keywords = {Artificial intelligence},
title = {Extraction of similarity based fuzzy rules from artificial neural networks},
doi = {10.1016/j.ijar.2006.04.003},
author = {Mantas Ruiz, Carlos Javier and Puche, J. M. and Mantas Ruiz, José Miguel},
}