基于神经网络的交通方式划分模型研究

Study on traffic mode-split based on neural network

在分析交通方式划分预测的一些基本理论的基础上,尝试应用概率神经网络进行交通方式划分建模,并给出了算例,分析表明该模型对交通方式划分问题不仅有很强的解释性,同时具有很好的可操作性。

Based on the analysis of some of the basic theories of traffic planning, this paper managed to use probabilistic neural network modeling traffic mode-split, and an example proved its correctness. The result shows that facing to the traffic mode-split problem, the model is not only very explanatory, but also has a good operability.