提出了一种新的动态交通拥挤预测模型。
This paper proposes a new dynamic traffic congestion prediction model.
动态交通信息的发布与预测是ITS的关键所在。
Distribution and prediction of dynamic traffic information is the key problem of ITS.
提出了一种新的基于移动检测技术、神经网络和模糊判断方法的城市路网动态交通拥挤预测模型。
A model for urban road network traffic congestion forecast based on probe vehicle technology, fuzzy logic judgement and back-propagation (BP) neural network was proposed.
实时、准确的交通量预测是实现动态交通流控制及诱导的前提和基础。
The accurate real-time forecast of traffic volume is the premise and basement of the dynamic traffic control and guidance.
提出了一种预测交通流量的动态组合建模方法。
A combined dynamic method of forecast traffic volume time series is proposed.
目前，车辆智能导航系统开发的一个难点是基于实时交通信息预测的动态路径规划。
At present, dynamic vehicle route planning based on real-time traffic information prediction is a difficult problem in the development of intelligent vehicle navigation system.
交通系统公路客运量预测不仅具有模糊性和动态性等特点，而且受多个因素影响。
The forecast of passenger capacity is not only obscure and dynamic in transportation system, but also influenced by several factors.
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.
短时交通流预测是动态交通控制和诱导的前提。
Short—term traffic flow prediction is the basis of dynamic traffic control and guidance.
其中，交通流预测尤其是短时交通流预测是动态路径规划中决定道路权重的重要因子。
Among them, traffic flow prediction especially short-term traffic flow prediction is an important factor, which decided the road weights in dynamic path planning.
其中，交通流预测尤其是短时交通流预测是动态路径规划中决定道路权重的重要因子。
Among them, traffic flow prediction especially short-term traffic flow prediction is an important factor, which decided the road weights in dynamic path planning.
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