Rule extraction from an artificial neural network based fault direction discriminator

This paper presents a technique for extracting rules from a multilayer feedforward neural network based fault direction discriminator. The techniques such as Karnaugh mapping technique and Quine McCluskey´s technique become complex and unmanageable as the number of inputs increase. An alternative technique is proposed where the weights are symbolically mapped such that positive and negative weights both could be considered based upon their absolute value