Application of Combined Forecasting Models to Intelligent Transportation Systems

摘要

Several combined forecasting techniques are investigated in this paper. Six baseline individual predictors are selected as basic combination components. Experimental results demonstrate that the combined predictors can significantly reduce error rates and provide a large improvement in stability and robustness. It reveals that the techniques are practically promising in the traffic domain.