提出用动态回归神经网络建立高速公路宏观交通流模型。
A dynamic recurrent neural network to freeway macroscopic traffic flow modeling is presented.
宏观角度的分析得出了该模型与宏观交通流模型基本规律的一致性，并得到了模型参数和交通参数之间的关系。
The results suggest that the HPN model accord with the fundamental laws of traffic flow model. And the relation between the variables of HPN model and traffic system is obtained.
根据理论基础和研究方法的不同，可以将各种交通流模型分为宏观模型、中观模型和微观模型。
According to theoretical basis and research methods, the traffic flow models can be classified into macroscopic, meso-scopic and microscopic ones.
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