Journal
DECISION SUPPORT SYSTEMS
Volume 46, Issue 1, Pages 411-419Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.dss.2008.07.009
Keywords
Fashion sales forecasting; Extreme learning machine; Artificial neural network; Backpropagation neural networks; Decision support system
Categories
Funding
- Research Grants Council of Hong Kong [PolyU5145/06E, PolyU5101/05E]
- Hong Kong Polytechnic University
Ask authors/readers for more resources
Sales forecasting is a challenging problem owing to the volatility of demand which depends on many factors. This is especially prominent in fashion retailing where a versatile sales forecasting system is crucial. This study applies a novel neural network technique called extreme learning machine (ELM) to investigate the relationship between sales amount and some significant factors which affect demand (such as design factors). Performances of our models are evaluated by using real data from a fashion retailer in Hong Kong. The experimental results demonstrate that our proposed methods outperform several sales forecasting methods which are based on backpropagation neural networks. (c) 2008 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available