A Forecasting Model Based Support Vector Machine and Particle Swarm Optimization

Authors:
Qi Wu;Hong-Sen Yan;Hong-Bing Yang
Affiliations:
-;-;-
Venue:
PEITS '08 Proceedings of the 2008 Workshop on Power Electronics and Intelligent Transportation System
Year:
2008

Citing 0
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Abstract

In view of the bad forecasting results of the standard v-support vector machine (SVM) for product sale series with the normal distribution noise, a SVM based on the Gaussian loss function named by g-SVM is proposed. And then, a hybrid forecasting model for product sales and its parameter-choosing algorithm are presented. The results of its application to car sale forecasting indicate that the short-term forecasting method based on g-SVM is effective and feasible.