On the Neural Network Modeling with Support Rough Set Theory
Xianghua Fu · Kongzhi yu juece · 2005
A method is introduced to cooperate the decision support and classification, in which rough set theory and neural network are formed integrated into a model. A neural network modelling way based on rough set theory is proposed. The neural network is preprocessed by the intelligent data analysis capability of rough set theory, and the key components are extracted as the inputs of the neural network to determine original topology of the rough neural network. Furthermore, the realization steps of the model are analyzed, and the rough neural network is trained with original data. The model constructed is applied to extraction of classification rules. The experimental results show that the model can increase the classification correctness effectively.