基于DGM(1,1)和GRNN的交通流联合预测模型

Zhiheng Yu, Kecheng Liu, Chengli Zhao, Y. Liu
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引用次数: 1

摘要

为了提高交通流的预测精度,本文提出了一种基于DGM(1,1)的残差校正组合预测模型。在引入DGM(1,1)的建模步骤后,建立了DGM- grnn组合模型。在模型中,使用GRNN来预测DGM(1,1)模型的残差。最后,对DGM(1,1)模型和残差修正模型的预测结果进行汇总,得到组合预测模型的最终预测结果。本文利用该模型对上三高速公路交通流进行了预测,并与DGM(1,1)的实验结果进行了比较。验证了该方法的有效性和可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combined Forecasting Model of Traffic Flow Based on DGM(1,1) and GRNN
In order to improve the prediction accuracy of traffic flow, this paper proposes a combined forecasting models with residual correction based on DGM(1,1). After introducing the modeling steps of DGM(1,1), DGM-GRNN combination model is established. In the model, the GRNN is used to predict the residual of DGM(1,1) model. Finally, we sum up the predict result of DGM(1,1) model and the residual correction model, and get the final prediction result of the combined forecasting model. We predicted the traffic flow of shangsan expressway by the model in this paper and then compared the results with the experimental results of DGM(1,1). The validity and feasibility of the proposed method are verified.
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