Review of the Self-Organizing Map (SOM) Approach in the Field of Environmental Engineering
B. Sowmiya1, S. Amal Raj2
1B. Sowmiya, Research Scholar, Centre for Environmental Studies, Anna University, Kotturpuram, Chennai (Tamil Nadu). India.
2Dr. S. Amal Raj, Professor, Centre for Environmental Studies, Anna University, Kotturpuram, Chennai (Tamil Nadu). India.
Manuscript received on July 25, 2016. | Revised Manuscript received on July 29, 2016. | Manuscript published on September 05, 2016. | PP: 32-37 | Volume-6 Issue-4, September 2016. | Retrieval Number: D2900096416/2016©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In environmental engineering field, the use of artificial neural networks (ANNs) has received steadily increasing interest over the last decade or so. In ANN, selforganizing map (SOM) is an unsupervised learning method to analyze, cluster, and model various types of large databases. There is, however, still a notable lack of comprehensive literature review for SOM along with training and data handling procedures, and potential applicability. As a result the present paper, first explains the basic structure and algorithm of selforganizing map (SOM) and secondly, to review published applications with special importance on environmental engineering related problems in order to assess how well SOM can be used to solve a particular problem. Finally, concluded that self-organizing map (SOM) is a hopeful technique suitable to investigate, model, and rule environmental related problems. However, in recent years, self-organizing map (SOM) has displayed a steady increase in the number of applications in environmental engineering related problems due to the robustness of the method.
Keywords: Linear and non- linear process, Artificial Neural Network, Self Organizing Map, Environmental Engineering, Review