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Research on Method of Double-Layers BP Neural Network in Prediction of Crossroads' Traffic Volume

机译:双层BP神经网络在十字路口交通量预测中的方法研究

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摘要

Intelligent transportation systems(ITS) is effective on solving the problem of traffic jam in cities. Prdiction of crossroads' traffic volume is the key technology in ITS. BP neural network is universally used in prediction of crossroads' traffic volume. This research aimed at using double-layers BP neural network to predict the traffic volume of Lishan Crossroad Jinan City. Results of the computer simulation showed that the method was applicable, the average relative tolerance was 9.71%. The doble-layers BP neural network can be used for prediction of crossroads' traffic volume.
机译:智能交通系统(ITS)可有效解决城市交通拥堵的问题。预测十字路口的交通流量是ITS中的关键技术。 BP神经网络普遍用于预测十字路口的交通流量。本研究旨在利用双层BP神经网络预测济南市梨山十字路口的交通量。计算机仿真结果表明该方法是可行的,平均相对公差为9.71%。双层BP神经网络可用于预测十字路口的交通流量。

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