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Prediction for Percentage of Vehicle Entering Expressway Rest Area Based on BP Neural Network

机译:基于BP神经网络进入高速公路休息区的车辆百分比预测

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In order to scientifically decide the percentage of vehicle entering expressway rest area, based on analyzing the influencing factors relating to the percent of mainline traffic stopping, a BP neural network prediction model for it was put forward. Finally, The Xinzheng Rest Area (XRA) was taken as an example for verifying the feasibility of the prediction model and determining the influence degree of the Shijiazhuang-Wuhan high-speed railway on the percentage of mainline vehicles entering XRA. The result shows that the model had a high precision and reliability.
机译:为了科学地决定进入高速公路休息区的车辆的百分比,基于分析与主线交通停止的百分比有关的影响因素,提出了一种BP神经网络预测模型。最后,鑫正休息区(XRA)是为了验证预测模型的可行性,并确定石家庄 - 武汉高速铁路对进入XRA的主线车辆百分比的影响。结果表明,该模型具有高精度和可靠性。

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