By clustering of traffic flow time series, the typical traffic fluctuation patterns can be found.
采用聚类分析方法对交通流时间序列进行分析可以发现典型的交通流变化模式。
Then the mechanism of the chaotic learning algorithm is described, and the adaptive learning algorithm of WNN for traffic flow time series is designed.
阐述了混沌学习算法的机理，设计了交通流量WNN混沌时间序列自适应学习算法。
In order to solve serious urban transport problems, according to the proved chaotic characteristic of traffic flow, a non linear chaotic model to analyze the time series of traffic flow is proposed.
为了解决日益严重的城市交通问题，本文根据交通流已被证明的混沌特性，尝试采用非线性混沌模型来分析交通流时间序列。
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