A Traffic Flow Forecasting Model Based on Variable Dimension Fractal Combined with Weekly Similarity

Abstract:

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It’s important that the short-time traffic flow forecasting has good real-time performance and high accuracy. In order to satisfy this demand, weekly similarity is imported and an improved fractal forecast model is established. In order to improve forecast accuracy furthermore, one-rank local-region forecasting principle is referenced to determine parameters which influence weekly similarity degree. Finally, the improved fractal model based on variable dimension is employed to predict the traffic flow in Hangzhou city. The experiment result shows that the improved fractal method proposed here possesses high forecast accuracy.

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Periodical:

Edited by:

Ran Chen

Pages:

3427-3432

DOI:

10.4028/www.scientific.net/AMM.44-47.3427

Citation:

H. Z. Dong et al., "A Traffic Flow Forecasting Model Based on Variable Dimension Fractal Combined with Weekly Similarity", Applied Mechanics and Materials, Vols. 44-47, pp. 3427-3432, 2011

Online since:

December 2010

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Price:

$35.00

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