Abstract
In this paper, after a review of traffic forecasting methods and the development of piecewise linear functions, a new traffic flow forecasting model based on adaptive hinging hyperplanes was proposed. Adaptive hinging hyperplanes (AHH) is a kind of piecewise linear models which can decide its division of the domain and the parameters adaptively. Acceptable results (forecasting error is smaller than 15%) were obtained in the test of the real traffic data in Beijing. After comparison with the results of prediction model base on MARS, the following conclusions can be drawn. First, the two methods have almost the same performance in prediction precision. Second, AHH will be a little more stable and cost less computing time. Thus, AHH model may be more applicable in practical engineering.
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Lu, Y., Hu, J., Xu, J., Wang, S. (2009). Urban Traffic Flow Forecasting Based on Adaptive Hinging Hyperplanes. In: Deng, H., Wang, L., Wang, F.L., Lei, J. (eds) Artificial Intelligence and Computational Intelligence. AICI 2009. Lecture Notes in Computer Science(), vol 5855. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05253-8_72
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DOI: https://doi.org/10.1007/978-3-642-05253-8_72
Publisher Name: Springer, Berlin, Heidelberg
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