Abstract
This work presents a hybrid expert system (HES) intended to minimise some complex problems pervasive to knowledge engineering such as: the knowledge elicitation process, known as the bottleneck of expert systems; the choice of a model for knowledge representation to codify human reasoning; the number of neurons in the hidden layer and the topology used in the connectionist approach; the difficulty to extract an explanation from the network. Two algorithms applied to developing of HES are also suggested. One of them is used to train the fuzzy neural network and the other to obtain explanations on how the fuzzy neural network attained a conclusion. A case study is presented (e.g. epileptic crisis) with the inclusion of problem definition and simulations. The results are also discussed.
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