A Hybrid Expert System for Error Message Classiication
نویسندگان
چکیده
A hybrid intelligent classiier is built for pattern classiication. It consists of a classiication and regression tree (CART), a genetic algorithm (GA) and a neural network (NN). CART extracts features of the patterns by setting up decision rules. Rule improvement by GA is explored. The rules act as a pre-processing layer of NN, a multi-class neural classiier, through which the most probable class is determined. A realistic test of classifying error messages generated from a telephone exchange shows that the CART-NN hybrid system has comparable performance with Bayesian neural network.
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تاریخ انتشار 1995