Prediction model of consumption data based on PCA-RKM-BP

This paper presents a new prediction model named PCA-RKM-BP model. The model combines principal component Analysis (PCA), K-means clustering based on the rough set (RKM) and the BP neural network, and it makes the principal component analysis result of data as neural network´s input, and chooses rough set result as the BP neural network´s hidden layer node center. The model makes full use of the advantages of the principal component analysis, rough set clustering and BP neural network, and it can effectively enhance the prediction accuracy. After using the new prediction model in consumption data, the experimental results show that the new prediction model has better prediction effect compared with the linear prediction method and traditional BP neural network.