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A novel method of rule extraction from artificial neural network with optimized activation function is proposed. Weight-decay approach is used in training and the unnecessary connections in the neural network are pruned at the cost of an increase in the error function within a predetermined limit. A penalty term is added in the activation function to facilitate the values of hidden and output nodes...
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