Application of SVR with Genetic optimization algorithm in urban traffic flow forecasting
Publish place: 3rd Conference on Financial Mathematics and Applications
Publish Year: 1391
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
CFMA03_150
تاریخ نمایه سازی: 16 خرداد 1394
Abstract:
Forecasting of inter-urban traffic flow has been one of the most important issues globally in the research on road traffic congestion. Due to traffic flow forecasting involves a rather complex nonlinear data pattern; there are lots of novel forecasting approaches to improve the forecasting accuracy. This investigation presents a short-term traffic forecasting model which combines the support vector regression (SVR) model with Genetic Optimization algorithms (SVRGA) to forecast inter-urban traffic flow. Additionally, a numerical example is employed to elucidate the forecasting performance of the proposed SVRGA model. Finally the results compare and their performance with time series models.
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Authors
Saifollah Saadatpishe
Department of Mathematics, Faculty of Basic Sciences, Shiraz University of Technology, Shiraz, Iran
Hamidreza Maleki
Department of Mathematics, Faculty of Basic Sciences, Shiraz University of Technology, Shiraz, Iran