Continuous ant colony optimization in a SVR urban traffic forecasting model

Authors:
Wei-Chiang Hong;Ping-Feng Pai;Shun-Lin Yang;Chien-Yuan Lai
Affiliations:
Department of Information Management, Oriental Institute of Technology, Taipei, Taiwan;Department of Information Management, National Chi Nan University, Nantou, Taiwan;Department of Industrial Engineering and Enterprise Information, Tung-Hai University, Taichung, Taiwan;Department of Information Management, Oriental Institute of Technology, Taipei, Taiwan
Venue:
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Year:
2007

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Abstract

Accurate forecasting of inter-urban traffic flow has been one of most important issues in the research on road traffic congestion. The traffic flow forecasting involves a rather complex nonlinear data pattern. Recently, support vector regression (SVR) model has been widely used to solve nonlinear regression and time series problems. This investigation presents a short-term traffic forecasting model which combines SVR model with continuous ant colony optimization (SVRCACO), to forecast inter-urban traffic flow. A numerical example of traffic flow values from northern Taiwan is employed to elucidate the forecasting performance of the proposed model. The simulation results indicate that the proposed model yields more accurate forecasting results than the seasonal autoregressive integrated moving average (SARIMA) time-series model.