According to the speciality of electricity demand development in a city, the grey neural network model GNNM (1, 1) was introduced into the field of city electricity demand forecasting in this paper.

针对城市电力系统年用电量增长的特点，将灰色神经网络模型GNNM(1,1)引入城市年用电量预测。

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Such as the return of specific prediction method, smoothing index, grey model prediction, BP neural network, RBF neural network .

具体如回归预测法、指数平滑法、灰色模型预测法、BP神经网络法、RBF神经网络法。

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It is found that it is better to predict the return rate with general regression neural network than with grey prediction and multiple regression model.

再以广义回归神经网络建立预测模型，与灰预测模型、多元回归模型进行预测能力及报酬率的比较分析。

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