Rule extraction from Boolean artificial neural networks

Abstract

Artificial neural networks (ANNs) are being widely used in many applications with competitive results. Few studies describe how the acquired information is represented by these structures, how we could extract that information and standard ways of analyzing the results. This work presents a guideline for extracting and modeling the knowledge acquired by Boolean ANNs (BANNs).