Abstract
As an artificial intelligent technique, artificial neural networks (ANNs) have been applied successfully in a wide range of fields due to its effective learning ability. In this paper, we conduct an empirical application on fragrance bottle form design due to its wide variety of appearances. For getting a better structure of the ANN model to develop the consumer-oriented expert system, we conduct 12 (=4*3) ANN models with four pairs of learning rate and momentum factors, and three widely used rules for determining the number of neurons in the single hidden layer. As a result, the HN1-C model getting the highest predicting accuracy rate (90.39%) is used to help product designers determine the optimal form combination of new product design.