基于Shapley值的西安市生活需水量组合预测研究

Research on combination forecast method in predication of domestic water demand in Xi'an based on shapley value

利用等维灰数递补法、非线性回归、广义回归神经网络等3种方法进行了西安市生活需水量预测,比较了不同方法的预测误差,然后根据各种方法对总预测值的信息贡献能力形成Shapley值组合需水量预测方法,计算了不同预测方法的Shapley值及其组合权重,形成组合预测需水量模型。预测结果表明:组合方法误差曲线平缓、平均误差值较小,具有一定的预测精度,适用于需水量的中短期预测。

The same dimension gray recurrence prediction,multiple nonlinear regression prediction,GRNN neural network prediction methods were done to get domestic water demand of Xi＇an,and then prediction error of different methods was compared.The paper proposect the combination forecast method based on shapely value which equal to the information contribtive ability of predictive value calculated the shapley value and combination weights of different forecast methods,formed combination forcast model for water demand.The result showed that the combination method had a smoothing error curve and a smaller average error value.It has a certain prediction accuracy and is applicable to water demand in the short-term water demand forecast.