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Research on demand forecast of vehicle turnover equipment based on GM(1,1)-BP combined model

机译:基于GM(1,1)-BP组合模型的车辆流动设备需求预测研究

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摘要

According to the historical data characteristics of vehicle turnover equipment demand,a GM(1,1)- BP combined model is established.Firstly,GM(1,1)model is used to forecast the historical data of vehicle turnover equipment demand.On this basis,BP neural network is introduced to correct the residual of the prediction.It optimizes the forecasting method of vehicle turnover equipment demand,makes up the deficiency of single model,and enhances the accuracy of vehicle turnover equipment demand forecasting.
机译:根据车辆周转设备需求的历史数据特征,建立了GM(1,1) - BP组合模型。首先,GM(1,1)模型用于预测车辆营业额设备需求的历史数据 基础上,引入了BP神经网络以校正预测的残余。它优化了车辆周转设备需求的预测方法,弥补了单一模型的缺点,提高了车辆周转设备需求预测的准确性。

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