Title :
Forecasting demand of short life cycle products by SVM
Author :
Xu Xian-hao ; Zhang Hao
Author_Institution :
Sch. of Manage., Huazhong Univ. of Sci. & Technol., Wuhan
Abstract :
In this paper, the demand of short life cycle products is forecasted by the method of SVM in the conditions of data deficiency. The method considers productspsila demand, demand forecasted by Bass model and season factor as affecting factors of the demand of short life cycle product, the training sample and forecasting sample varies when the time changes. Then SVM forecasting model is set up and with it the demand is forecasted. The comparison with relative models indicates that the presented method is more valid in forecasting the demand of short life cycle products.
Keywords :
economic forecasting; product life cycle management; support vector machines; SVM; demand forecasting; short life cycle products; support vector machine; Conference management; Demand forecasting; Economic forecasting; Engineering management; Pattern recognition; Predictive models; Support vector machine classification; Support vector machines; Technology forecasting; Technology management; SVM; bass model; forecasting; short life-cycle products;
Conference_Titel :
Management Science and Engineering, 2008. ICMSE 2008. 15th Annual Conference Proceedings., International Conference on
Conference_Location :
Long Beach, CA
Print_ISBN :
978-1-4244-2387-3
Electronic_ISBN :
978-1-4244-2388-0
DOI :
10.1109/ICMSE.2008.4668939
