An Improved Double-layer K-nearest Neighbor Nonparametric Regression Method for Short-time Traffic Flow Prediction

Wang Cheng, Pang Xiyu, Huang Guolin

Abstract


In combination with the repeatability of the traffic flow state patterns, this article improved the k-nearest neighbor non-parametric regression method. To be specific, the neighbors were screened twice and the function based on state pattern recognition was introduced; moreover, the traffic flows in the past time and the traffic flows towards the related directions at both upstream and downstream crossroads were taken into account, so that the predictive ability of the proposed k-nearest neighbor non-parametric regression method can be improved. In addition, the final prediction results were output using the weighted average method of the reciprocal of the state pattern vector matching distance, so as to enhance the accuracy and real-time performance of the short-term traffic flow prediction.

Keywords


Traffic flow;Double-layer;State pattern;Non-parametric

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DOI: http://dx.doi.org/10.12928/telkomnika.v14i2A.4332

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TELKOMNIKA Telecommunication, Computing, Electronics and Control
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