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With the rapid development of online shopping, the ability to intelligently collect and analyze information about E-shoppers has become a key source of competitive advantage for firms. This paper presents a optimal algorithm of modeling dynamic architecture for Artificial Neural Networks (ANN) and a novel machine-learning algorithm for extracting rules from databases via using genetic algorithm. In the dynamic architecture, the number of hidden layers and the number of hidden nodes are sequentially and dynamically generated until a level of performance accuracy is reached.
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