Title :
Daily visitor volume forecasts for Expo 2010 Shanghai China
Author_Institution :
Shanghai Municipal Transp. Inf. Center, Shanghai Urban & Rural Constr. & Transp. Comm., Shanghai, China
Abstract :
The long term and great number of visitors to World Exposition 2010 Shanghai China (World Expo 2010) brought additional pressure to the regular urban traffic. This study provided daily visitor volume forecasts before the Expo Site opened each day. Related government departments benefited from the prediction in the management of Expo park service system and transportation scheduling. According to the natural classification of expo visitors into individuals and groups, the letter applied a hybrid methodology of fuzzy Takagi-Sugeno (T-S) models and linear least squares regression (LLSR) model to obtain the forecasts. The proposed approach showed the capacity of highly accurate prediction and remarkable robustness. And the results were timely issued through the Comprehensive Transportation Information Platform (CTIP) to the Shanghai government and Bureau of Shanghai World Expo Coordination for reference.
Keywords :
fuzzy set theory; least squares approximations; regression analysis; transportation; Bureau of Shanghai World Expo Coordination; Comprehensive Transportation Information Platform; Expo 2010 Shanghai China; Expo park service system; Shanghai government; World Expo 2010; daily visitor volume forecasts; expo visitors; fuzzy Takagi-Sugeno models; linear least squares regression model; transportation scheduling; urban traffic; Correlation; Forecasting; Mathematical model; Predictive models; Roads; Training data;
Conference_Titel :
Intelligent Transportation Systems (ITSC), 2011 14th International IEEE Conference on
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4577-2198-4
DOI :
10.1109/ITSC.2011.6082994