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。
Based on local linear prediction model of chaotic time series, short-term load forecasting method on multi-embedding dimension is presented.
基于混沌时间序列的局域线性预测模型，提出了多嵌入维的短期负荷预测方法。
We present a linearly regressive prediction model for noisy chaotic time series phase space based on variational Bayesian and phase space reconstructive theory.
基于变分贝叶斯及相空间重构理论，提出了含噪混沌时间序列相空间域线性回归预测模型。
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