A Hybrid Sales Forecasting Scheme by Combining Independent Component Analysis with K-Means Clustering and Support Vector Regression
Sales forecasting plays an important role in operating a business since it can be used to determine the required inventory level to meet consumer demand and avoid the problem of under/overstocking. Improving the accuracy of sales forecasting has become an important issue of operating a business. Thi...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/624017 |
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| _version_ | 1832563201369178112 |
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| author | Chi-Jie Lu Chi-Chang Chang |
| author_facet | Chi-Jie Lu Chi-Chang Chang |
| author_sort | Chi-Jie Lu |
| collection | DOAJ |
| description | Sales forecasting plays an important role in operating a business since it can be used to determine the required inventory level to meet consumer demand and avoid the problem of under/overstocking. Improving the accuracy of sales forecasting has become an important issue of operating a business. This study proposes a hybrid sales forecasting scheme by combining independent component analysis (ICA) with K-means clustering and support vector regression (SVR). The proposed scheme first uses the ICA to extract hidden information from the observed sales data. The extracted features are then applied to K-means algorithm for clustering the sales data into several disjoined clusters. Finally, the SVR forecasting models are applied to each group to generate final forecasting results. Experimental results from information technology (IT) product agent sales data reveal that the proposed sales forecasting scheme outperforms the three comparison models and hence provides an efficient alternative for sales forecasting. |
| format | Article |
| id | doaj-art-0f9e985d47134686bf3f9b29157d034a |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-0f9e985d47134686bf3f9b29157d034a2025-02-03T01:20:40ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/624017624017A Hybrid Sales Forecasting Scheme by Combining Independent Component Analysis with K-Means Clustering and Support Vector RegressionChi-Jie Lu0Chi-Chang Chang1Department of Industrial Management, Chien Hsin University of Science and Technology, Taoyuan County 32097, TaiwanSchool of Medical Informatics, Chung Shan Medical University, Information Technology Office, Chung Shan Medical University Hospital, Taichung City 40201, TaiwanSales forecasting plays an important role in operating a business since it can be used to determine the required inventory level to meet consumer demand and avoid the problem of under/overstocking. Improving the accuracy of sales forecasting has become an important issue of operating a business. This study proposes a hybrid sales forecasting scheme by combining independent component analysis (ICA) with K-means clustering and support vector regression (SVR). The proposed scheme first uses the ICA to extract hidden information from the observed sales data. The extracted features are then applied to K-means algorithm for clustering the sales data into several disjoined clusters. Finally, the SVR forecasting models are applied to each group to generate final forecasting results. Experimental results from information technology (IT) product agent sales data reveal that the proposed sales forecasting scheme outperforms the three comparison models and hence provides an efficient alternative for sales forecasting.http://dx.doi.org/10.1155/2014/624017 |
| spellingShingle | Chi-Jie Lu Chi-Chang Chang A Hybrid Sales Forecasting Scheme by Combining Independent Component Analysis with K-Means Clustering and Support Vector Regression The Scientific World Journal |
| title | A Hybrid Sales Forecasting Scheme by Combining Independent Component Analysis with K-Means Clustering and Support Vector Regression |
| title_full | A Hybrid Sales Forecasting Scheme by Combining Independent Component Analysis with K-Means Clustering and Support Vector Regression |
| title_fullStr | A Hybrid Sales Forecasting Scheme by Combining Independent Component Analysis with K-Means Clustering and Support Vector Regression |
| title_full_unstemmed | A Hybrid Sales Forecasting Scheme by Combining Independent Component Analysis with K-Means Clustering and Support Vector Regression |
| title_short | A Hybrid Sales Forecasting Scheme by Combining Independent Component Analysis with K-Means Clustering and Support Vector Regression |
| title_sort | hybrid sales forecasting scheme by combining independent component analysis with k means clustering and support vector regression |
| url | http://dx.doi.org/10.1155/2014/624017 |
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