Intelligent multivariate sales forecasting using wrapper approach and neural networks

摘要：

This research investigated a retail sales forecasting problem based on early sales. An effective multivariate intelligent decision-making (MID) model is developed to handle this problem by integrating a data preparation and preprocessing module, a harmony search-wrapper-based variable selection (HWVS) module and a multivariate intelligent forecaster (MIF) module. The HWVS module selects out the optimal input variable subset from given candidate inputs as the inputs of MIF. The MIF is proposed to model the relationship between the selected input variables and the sales volumes of retail products, and then employed to forecast the sales volumes of retail products. Experiments were conducted to evaluate the effectiveness of the proposed model. Results show that it is statistically significant that the proposed MID model can provide superior forecasts to ELM-based model and generalized linear model.

关键词： retail industry multivariate forecasting early sales

作者: Z. X. Guo Min Li W. K. Wong Z. X. Guo,

作者单位: Institute of Textiles and Clothing,The Hong Kong Polytechnic University,Hunghom, Kowloon, Hong Kong, Business School, Sichuan University, Wuhou District, Chengdu, Sichuan, P. R. China

会议类型: 国际会议

会议名称: IEEE 10th International Conference on Industrial Informatics(第十届IEEE工业信息学国际学术会议 INDIN2012)

会议地点: 北京

会议语种:英文

页码: 145-150

在线出版日期: 2012-07-25（万方平台首次上网日期，不代表论文的发表时间）