Knowledge manipulation in a Hebbian network for fault diagnosis

Recently research on hybrid solutions for fault diagnosis problems. In this paper we propose a neural network implementation of diagnosis systems. Based on certainty factor modeling and Hebbian learning, the network features with local learning ability, quasi-causal representation of diagnosis process, and easy mechanism of knowledge manipulation.