The freeway network in China is rapidly developing, causing a lot of problems about maintenance and management.
我国公路建设在飞速发展的同时，大量的养护、管理问题也随之出现。
This paper puts forward the four key questions which are layout, gross, scale and sequence of the freeway network planning.
提出高速公路网规划的布局、总量、规模和序列四大关键问题。
Under the uniformly congested freeway and selecting appropriate flow density function, a freeway network flow model is constructed.
考虑快速路一致拥挤的前提下，通过选取适当的流—密关系式，建立快速路网络流模型。
By analyzing the freeway macroscopic dynamic traffic flow model, the paper presents a neural network model for traffic flow.
通过对高速公路宏观动态交通流模型的分析，提出了动态交通流的神经网络模型。
Secondly, the identifying model of freeway hazardous location in mountainous areas was established based on BP neural network.
其次，建立了基于BP神经网络的山区高速公路事故多发点鉴别模型。
The variable speed control for freeway traffic is a nonlinear and time variable system, it is difficult to model with a mathematical model. A neural network control method is put forward.
针对高速公路可变速度控制是一个非线性时变系统，难于用数学模型准确建模这一特点，提出了神经网络控制方法。
A dynamic recurrent neural network to freeway macroscopic traffic flow modeling is presented.
提出用动态回归神经网络建立高速公路宏观交通流模型。
The control for speed limitation on freeway is a nonlinear and time variable system, it is difficult to model with a mathematical model. A control method based on RBF Neural Network is put forward.
针对高速公路限速控制是一个非线性时变系统、难以用数学模型准确建模这一特点，提出了R BF神经网络控制方法。
Then, the BP neural network is trained by using traffic flow data from a section of freeway and the network model parameters can be obtained.
并利用一段高速公路的交通流数据对BP神经网络进行训练，得到网络参数。
Then, the BP neural network is trained by using traffic flow data from a section of freeway and the network model parameters can be obtained.
并利用一段高速公路的交通流数据对BP神经网络进行训练，得到网络参数。
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