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《Mathematics in Practice and Theory》 2008-11
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A Real-Time forecast Model of Traffic Information Based on On-Line Training

CAO Kai,LI Shi-ming(School of Traffic and Vehicle Engineering,Shandong University of Technology,Zibo 255049,China)  
Forecast accuracy and time efficiency are couple of contradictions to be hard to resolve for real-time traffic information prediction.In order to improve time efficiency of forecast,we toke an accurate on-line support vector regression(AOSVR) as a basis developing real-time traffic information forecast model,and proposed a simplified computing method of sigmoid kernel based on cloud model.The applied results indicated that proposed approach obviously improved the forecast time efficiency of AOSVR model in spite of small decrease in prediction precision for simplifying computing of sigmoid kernel.
【CateGory Index】: U491.14
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