Research on Classification of E-Shopper Based on Neural Networks

The present algorithms for artificial neural networks, to a certain extent, have various questions such as computational complexity, low accuracy and narrow scope of application. This paper presents a new algorithm for extracting accurate and comprehensible rules from databases via trained artificial neural network (ANN) using genetic algorithm. The new algorithm does not depend on the ANN training algorithms; also it does not modify the training results. The genetic algorithm is used to find the optimal values of input attributes (chromosome), X-m, which maximize the output function phi(k) of output node k. The function phi(k), is nonlinear exponential function. The optimal chromosome is decoded and used to obtain a rule belonging to class k. The good result is achieved by applying the new algorithm to a given database for customers buying computer.