基于灰色预测和神经网络的城市建设用地量预测

QUANTITY FORECASTING URBAN BUILDING LAND OF BASED ON THE COMBINATION OF GRAY FORECAST AND ARTIFICIAL NEURAL NETWORKS

采用灰色预测和NARMA(p,q)递归网络模型预测相结合的方法,对城市建设用地量预测值进行神经网络组合预测,在杭州市的实际应用中得到了较好的结果。

Based on the combination of gray forecast and NARMA(p,q) recurrent network model forecast, a new neural network forecasting method for urban building land quantity forecasting is proposed. This method is tested on the building lands of Hangzhou city and the results indicate that the method is effective and applicable.