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。
By analyzing the freeway macroscopic dynamic traffic flow model, the paper presents a neural network model for traffic flow.
以高速公路宏观动态交通流模型为原型，利用分段辨识法分析了高速公路交通流特性。
It takes the expressway macro dynamic traffic flow model as prototype and analyzes the characteristics of expressway traffic flow with "Segment Identification Method".
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.
并重点研究了基于遗传—bp神经网络组合模型的二源、三源动态交通流数据融合技术。
Further, the dynamic traffic data fusion technique based on the GA-BP Model is studied for the dual-source and triple-source dynamic traffic data.
对基于元胞自动机的交通流动力学模型和动态交通控制模型进行了综述。
Secondly, the paper summarized the traffic flow dynamics model and dynamic traffic control model based on Cellular Automata.
建立了一个基于多车道动态离散交通流模型的高速公路入口匝道流量优化控制模型。
An optimal control model of on-ramp metering was constructed, which was based on the dynamic discrete traffic flow model in multilane freeway.
根据常用的高速公路交通流宏观动态模型，建立了高速公路交通流的RBF神经网络模型。
On the basis of macroscopic dynamic traffic flow model which is frequently used in traffic control, Radial basis Function (RBF) neural network is designed.
交通网络模型、路径规划算法以及交通流预测是车辆导航动态路径规划需要解决的重点问题。
The key problems of vehicle navigation dynamic path planning are traffic network model, path planning algorithm and traffic flow prediction.
交通网络模型、路径规划算法以及交通流预测是车辆导航动态路径规划需要解决的重点问题。
The key problems of vehicle navigation dynamic path planning are traffic network model, path planning algorithm and traffic flow prediction.
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