神经网络模型在农村人均收入预测中的应用

FORECASTING THE AVERAGE INCOME OF FARMERS BASED ON ARTIFICIAL NEURAL NETWORK

利用人工神经网络建立了具有时间序列对象的预测模型，并提出了基于本模型的数据处理方法，在此基础上，对吉林省榆树县大坡镇两家村的人均收入进行了预测，证实了本模型的正确性和科学性。

The paper successfully makes the time series be the model couples of input and output of artificial neural network, and so suggests the forecasting model about average incomes of farmers by using artificial neural network model, and provides a data processing method and new Back Propagation algorithm based on this model. And introduces the programme about constructing forecasting model. At last forecasts the average income of farmers of Liangjia unit in Jilin Province, the forecasting values are creditable, the largest relative difference between forecasting value and original value is 0.78%. It verifies the model and its data processing method are scientific.