Applying Different Independent Component Analysis Algorithms and Support Vector Regression for IT Chain Store Sales Forecasting
Joint Authors
Lu, Chi-Jie
Wu, Jui-Yu
Dai, Wensheng
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-05
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Sales forecasting is one of the most important issues in managing information technology (IT) chain store sales since an IT chain store has many branches.
Integrating feature extraction method and prediction tool, such as support vector regression (SVR), is a useful method for constructing an effective sales forecasting scheme.
Independent component analysis (ICA) is a novel feature extraction technique and has been widely applied to deal with various forecasting problems.
But, up to now, only the basic ICA method (i.e., temporal ICA model) was applied to sale forecasting problem.
In this paper, we utilize three different ICA methods including spatial ICA (sICA), temporal ICA (tICA), and spatiotemporal ICA (stICA) to extract features from the sales data and compare their performance in sales forecasting of IT chain store.
Experimental results from a real sales data show that the sales forecasting scheme by integrating stICA and SVR outperforms the comparison models in terms of forecasting error.
The stICA is a promising tool for extracting effective features from branch sales data and the extracted features can improve the prediction performance of SVR for sales forecasting.
American Psychological Association (APA)
Dai, Wensheng& Wu, Jui-Yu& Lu, Chi-Jie. 2014. Applying Different Independent Component Analysis Algorithms and Support Vector Regression for IT Chain Store Sales Forecasting. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1049640
Modern Language Association (MLA)
Dai, Wensheng…[et al.]. Applying Different Independent Component Analysis Algorithms and Support Vector Regression for IT Chain Store Sales Forecasting. The Scientific World Journal No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-1049640
American Medical Association (AMA)
Dai, Wensheng& Wu, Jui-Yu& Lu, Chi-Jie. Applying Different Independent Component Analysis Algorithms and Support Vector Regression for IT Chain Store Sales Forecasting. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1049640
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1049640