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Cluster analysis in industrial market segmentation through artificial neural network |
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| Authors: | R J Kuo L M Ho C M Hu |
| Affiliation: | a Department of Industrial Engineering, National Taipei University of Technology, 1 Section 3, Chung-Hsiao East Road, Taipei 106, Taiwan, ROC b Department of Leisure, Recreation and Tourism Management, Shu-Te University, Kaohsiung County 824, Taiwan, ROC c Division of System Information, Foxconn Industrial PCE Production Group, Hsing-Chu, Taiwan, ROC |
| Abstract: | Market segmentation has commonly applied cluster analysis. This study intends to make the comparison of conventional two-stage method with proposed two-stage method through the simulated data. The proposed two-stage method is the combination of self-organizing feature maps and K-means method. The simulation results show that the proposed scheme is better than the conventional two-stage method based on the rate of misclassification. |
| Keywords: | Market segmentation Cluster analysis Monte Carlo simulation Self-organizing feature maps K-means |
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