本文通过实地调查获取的交通流量数据，分别采用移动平均法、指数平滑法、AR模型法三种交通流预测方法进行短时交通流量预测。
Through the data obtained by fieldwork, the paper forecasts the short-term traffic by three methods: moving-average method, index-smoothing method, AR model method.
在简要介绍神经网络原理的基础上，分析了采用神经网络解决交通系统中空车调度及交通流预测的原理及方法。
Based on the introduction to neural network principle, two methods of solving free train schedule and traffic flow prediction in transportation system with neural network are analyzed.
针对当前道路交通流量预测的多种不同特性的方法，提出了一种组合预测方法。
In response to various characteristics of the present road traffic flow prediction, a combined prediction is presented in this article.
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