关键词: 短期交通流预测, 霍特指数平滑法, 人工神经网络, 周相似, 组合方法

Abstract: Weekly similarity time series are constructed based on the weekly similarity of traffic flow. The Holt’s Exponential Smoothing（ES） method is employed to produce the forecasts for the weekly similarity time series,and Artificial Neural Network （ANN） method is used to produce the forecasts for the residual time series.The hybrid approach combining both ES and ANN makes use of the advantages of each method,so as to produce better prediction than that from single method.Experimental results with real data sets indicate that the combined method can produce more accurate predictions than that from ARIMA model or ANN alone.The hybrid model can be used for real-time short-term traffic flow forecasting.

Key words: short-term traffic flow forecasting, Holt’s exponential smoothing method, Artificial Neural Network, weekly similarity, hybrid approach