Method named BAYESIAN combined neural network model is proposed for short term traffic flow prediction in this paper.
提出一种新的贝叶斯组合神经网络模型并将其应用于短期交通流量的预测。
A large number of techniques have been applied into short-term traffic flow prediction, which can be classified into two groups: statistical models and artificial neural network model.
介绍了用于短期交通流预测的两大类模型：统计预测算法和人工神经网络模型。
Short—term traffic flow prediction is the basis of dynamic traffic control and guidance.
短时交通流预测是动态交通控制和诱导的前提。
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。
Research on the passenger flow prediction mainly concentrate on medium and long term prediction in the current, less involved short term prediction for delicated demand.
客运专线的短期客流预测研究较少，现存的研究多以中长期的预测方法为主，不能做到对旅客需求精细预测的要求。
Research on the passenger flow prediction mainly concentrate on medium and long term prediction in the current, less involved short term prediction for delicated demand.
客运专线的短期客流预测研究较少，现存的研究多以中长期的预测方法为主，不能做到对旅客需求精细预测的要求。
应用推荐