摘要
交通流量预测是智能运输系统的一个重要组成内容，但传统的数学方法一直未能取得令人满意的预测效果。信息融合技术是最近十多年来新兴的技术。它通过合理协调多源数据，充分综合有用信息，在较短的时间内，以较小的代价获得对未来交通流量的预测。实验证明，借助信息融合理论建立的聚类分析模型和神经网络模型对未来交通流量的预测比较准确，有实际意义。
Traffic volume detection is one of the important components of ITS. However, the satisfying results of detection cannot be given by the classic mathematical methods. The technology of information fusion is rising in this decade Harmonizing the information from several resources reasonably and taking full advantage of the useful information can work out the future traffic volume detection in a shorter time and less costs. Experiments show that the model of clustering analysis and the model of neural network in virtue of information fusion theories can put up an accurate detection of future traffic volume and thus they are practical.
关键词
信息融合
交通流预测
聚类分析
神经网络
Information fusion, Traffic forecasting, Clustering analysis, Neural network
