Title :
Forecast and Application of Chinese Automobile Production Based on SVM
Author :
Dong, Liangcai ; Xu, Ziqi
Author_Institution :
Logistics Eng. Sch., Shanghai Maritime Univ., Shanghai, China
Abstract :
Forecasting techniques are playing an increasingly important role in business decision-making. The study focusing on the forecast of Chinese automobile monthly production will be conducted in this paper. The Forecasting model is designed by using the method of Support Vector Machines, compared with the methods of ARIMA the results show that the SVM model has a more accurate prediction of performance.
Keywords :
automobile industry; decision making; support vector machines; Chinese automobile monthly production; SVM; business decision-making; forecasting techniques; support vector machines; Correlation; Forecasting; Kernel; Predictive models; Production; Support vector machines; Vehicles;
Conference_Titel :
Circuits, Communications and System (PACCS), 2011 Third Pacific-Asia Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4577-0855-8
DOI :
10.1109/PACCS.2011.5990153
