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

Abstract:

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.

• Periodical: Applied Mechanics and Materials (Volumes 44-47)
• Pages: 3427-3432
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.44-47.3427
• Online since: December 2010
• Authors: Hong Zhao Dong, Jian Jun Xu, Shuai Ma
• Keywords: Fractal Forecast, Short-Time Forecasting, Traffic Flow, Weekly Similarity Degree

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