Real Estate Price Indices Forcast by Using Wavelet Neural Network
Peng Tian · Jisuanji fangzhen · 2005
As real estate price indices play more significant roles, it is necessary to give more effective method for forecasting real estate price indices. By exploiting the data from the Shanghai housing price index of China Real Estate Index System (CREIS), this paper presents a wavelet neural network (WNN) model to give its forecasting. The comparisons among WNN, the exponential smoothing and RBF neural network, which are widely applicable, show that the forecasting of the WNN model is more effective given the large sample.