Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
385739 | Expert Systems with Applications | 2011 | 8 Pages |
Abstract
The difficulty with fashion retail forecasting is due to a number of factors such as the season, region and fashion effect and causes a nonlinear change in the original sales rules. To improve the accuracy of fashion retail forecasting, a two-stage dynamic forecasting model is proposed, which is combined with both long-term and short-term predictions. The model introduces the improved adjustment methods, the main adjustment model and error forecasting model in the adjustment system collaborated with each other. The real-time data are demonstrated by applying the model in wireless mobile environment. The experiment shows that the model provides good results for fashion retail forecasting.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Yanrong Ni, Feiya Fan,