DocumentCode :
2748049
Title :
Research on vessel price interval forecasting model based on the rough insensitive loss function SVR
Author :
Tianyi, Zhang ; Shengxiang, Sun
Author_Institution :
Department of Equipment Economics and Management, Naval Univ. of Engineering, Wuhan, P.R. China
fYear :
2011
fDate :
16-17 July 2011
Firstpage :
315
Lastpage :
318
Abstract :
Because the continually fluctuant price of vessel, the forecast of interval price is more dependable than precise data. A arithmetic of the rough ε-insensitive loss function-based support vector machines is introduced, which is able to forecast the interval value. In order to improve the precision of forecast, parameters of the arithmetic is optimized by chaos traverse. On the way, fore-learning objective function is established, to replace the minimum training error object function which easily leads to over training. According to above, the forecasting model of the vessel interval price is founded. Experimental results show that this RSVR model can forecast the vessel interval price has a high precision, and the fore-learning objective can reduce the over-training problems.
Keywords :
interval forecast; objective function; parameter selection; rough pattern; support vector regression;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Product Innovation Management (ICPIM), 2011 6th International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4577-0359-1
Type :
conf
DOI :
10.1109/ICPIM.2011.5983581
Filename :
5983581
Link To Document :
بازگشت