Identifying Model of Industry Clusters Life Cycle Based on RS-ANN

On the basis of integration of rough sets (RS) and RBF Artificial neural network (ANN), a model is constructed to identify the industry clusters life cycle. Firstly, the continuous attribute values are discretized using fuzzy clustering algorithm based on maximum discernibility value (MDV) search method and information entropy. And then the major attributes are reduced by rough sets. At last, taking 138 industry clusters as samples, the RBF neural network is trained with training samples and life cycle stages of testing samples are identified. The empirical results show that the fuzzy clustering algorithm based on MDV and information entropy can improve the discretization performance effectively, and the integration model of rough sets and neural network, the predicting precision of which is high, is an efficient and practical tool to identify industry clusters life cycle.