刊名:Physica A: Statistical Mechanics and its Applications
出版年:2017
出版时间:15 January 2017
年:2017
卷:466
期:Complete
页码:422-434
全文大小:3239 K
文摘
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A multiple sources and multiple measures based traffic flow prediction algorithm using the chaos theory and support vector regression method is proposed.
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The chaotic characteristics of traffic flow associated with the speed, occupancy, and flow are identified using the maximum Lyapunov exponent.
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The phase space of multiple measures chaotic time series are reconstructed based on the phase space reconstruction theory.
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The support vector regression (SVR) model is designed to predict the traffic flow.
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Results show that the proposed method has better performance in terms of the accuracy and timeliness.
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