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Research on Urban Traffic Flow Intelligent Prediction Based on Improved BP Artificial Neural Network

机译:基于改进BP人工神经网络的城市交通流智能预测研究

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摘要

The traffic flow is interrelated to traffic congestion, the big traffic flow directly results in traffic congestion of some section. In this paper on the basis of the research of overseas traffic accident, considering the characteristic of Chinese traffic, artificial neural network is used to predict traffic accident, a improved BP artificial neural network model according with Chinese the situation of a country is proposed. The urban traffic flow prediction is simulated under the particular situation, the result of the simulation shows that the improved BP artificial neural network shown in this paper can fit the urban traffic flow prediction very well and have high performance.
机译:交通流量与交通拥堵相互关联,大流量流直接导致某些部分的交通拥堵。本文在海外交通事故研究的基础上,考虑到中国交通的特点,人工神经网络用于预测交通事故,改进的BP人工神经网络模型根据中国的情况提出了一个国家的情况。在特定情况下模拟了城市交通流量预测,仿真结果表明,本文所示的改进的BP人工神经网络可以非常好地适应城市交通流量预测,具有高性能。

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