A Three-layered Self-Organizing Map Neural Network for Clustering Analysis
In the commercial world today, holding the effective information through information technology (IT) and the internet is a very important indicator of whether an enterprise has competitive advantage in business. Clustering analysis, a technique for data mining or data analysis in databases, has been...
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| Format: | Article |
| Language: | English |
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International Institute of Informatics and Cybernetics
2003-12-01
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| Series: | Journal of Systemics, Cybernetics and Informatics |
| Subjects: | |
| Online Access: | http://www.iiisci.org/Journal/CV$/sci/pdfs/P568803.pdf
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| _version_ | 1818243089701011456 |
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| author | Sheng-Chai Chi Chi-Chung Lee Tung-Chang Young |
| author_facet | Sheng-Chai Chi Chi-Chung Lee Tung-Chang Young |
| author_sort | Sheng-Chai Chi |
| collection | DOAJ |
| description | In the commercial world today, holding the effective information through information technology (IT) and the internet is a very important indicator of whether an enterprise has competitive advantage in business. Clustering analysis, a technique for data mining or data analysis in databases, has been widely applied in various areas. Its purpose is to segment the individuals in the same population according to their characteristics. In this research, an enhanced three-layered self-organizing map neural network, called 3LSOM, is developed to overcome the drawback of the conventional two-layered SOM through sight-inspection after the mapping process. To further verify its feasibility, the proposed model is applied to two common problems: the identification of four given groups of work-part images and the clustering of a machine/part incidence matrix. The experimental results prove that the data that belong to the same group can be mapped to the same neuron on the output layer of the 3LSOM. Its performance in clustering accuracy is good and is also comparable with that of the FSOM, FCM and k-Means. |
| first_indexed | 2024-12-12T13:55:35Z |
| format | Article |
| id | doaj.art-8a7fa69bb37f49e6a210594e219864f2 |
| institution | Directory Open Access Journal |
| issn | 1690-4524 |
| language | English |
| last_indexed | 2024-12-12T13:55:35Z |
| publishDate | 2003-12-01 |
| publisher | International Institute of Informatics and Cybernetics |
| record_format | Article |
| series | Journal of Systemics, Cybernetics and Informatics |
| spelling | doaj.art-8a7fa69bb37f49e6a210594e219864f22022-12-22T00:22:28ZengInternational Institute of Informatics and CyberneticsJournal of Systemics, Cybernetics and Informatics1690-45242003-12-01162433A Three-layered Self-Organizing Map Neural Network for Clustering AnalysisSheng-Chai Chi0Chi-Chung Lee1Tung-Chang Young2 Department of Industrial Management, Huafan University Department of Industrial Management, Huafan University Department of Industrial Management, Huafan University In the commercial world today, holding the effective information through information technology (IT) and the internet is a very important indicator of whether an enterprise has competitive advantage in business. Clustering analysis, a technique for data mining or data analysis in databases, has been widely applied in various areas. Its purpose is to segment the individuals in the same population according to their characteristics. In this research, an enhanced three-layered self-organizing map neural network, called 3LSOM, is developed to overcome the drawback of the conventional two-layered SOM through sight-inspection after the mapping process. To further verify its feasibility, the proposed model is applied to two common problems: the identification of four given groups of work-part images and the clustering of a machine/part incidence matrix. The experimental results prove that the data that belong to the same group can be mapped to the same neuron on the output layer of the 3LSOM. Its performance in clustering accuracy is good and is also comparable with that of the FSOM, FCM and k-Means.http://www.iiisci.org/Journal/CV$/sci/pdfs/P568803.pdf Self-Organizing Map (SOM)Neural NetworkPart Family/Machine Cell FormationThree-layered SOMClustering Analysis |
| spellingShingle | Sheng-Chai Chi Chi-Chung Lee Tung-Chang Young A Three-layered Self-Organizing Map Neural Network for Clustering Analysis Journal of Systemics, Cybernetics and Informatics Self-Organizing Map (SOM) Neural Network Part Family/Machine Cell Formation Three-layered SOM Clustering Analysis |
| title | A Three-layered Self-Organizing Map Neural Network for Clustering Analysis |
| title_full | A Three-layered Self-Organizing Map Neural Network for Clustering Analysis |
| title_fullStr | A Three-layered Self-Organizing Map Neural Network for Clustering Analysis |
| title_full_unstemmed | A Three-layered Self-Organizing Map Neural Network for Clustering Analysis |
| title_short | A Three-layered Self-Organizing Map Neural Network for Clustering Analysis |
| title_sort | three layered self organizing map neural network for clustering analysis |
| topic | Self-Organizing Map (SOM) Neural Network Part Family/Machine Cell Formation Three-layered SOM Clustering Analysis |
| url | http://www.iiisci.org/Journal/CV$/sci/pdfs/P568803.pdf
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