Application of DM and Combined Grey Neural Network in E-Commerce Data Transmission

Using grey system (GS) theory, data mining (DM) and radial basis function (RBF) neural network method, a new model, the combined grey neural network (CGNN) model is setup, which aims at solving users' data transmission in E-commerce. The results show that, in short-term prediction of data transmission, GM is an effective way and RBF has perfect ability to study and map. CGNN model and neural network have dual properties of trend and fluctuation under the condition of combining with the time-dependent sequence data. It is concluded that great improvement, comparing with trend prediction and simple factor in CGNN model, has been made to analyze data transmission.