Clustering of volcanic ash arising from different fragmentation mechanisms using Kohonen self-organizing maps

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• 作者：Orkun Ersoy ; Erkan Aydar ; Alain Gourgaud ; Harun Artuner ; Hasan Bayhan
• 关键词：Neural networks ; Kohonen self-organizing maps ; Volcanic ash ; Nemrut
• 刊名：Computers and Geosciences
• 出版年：2007
• 出版时间：June 2007
• 年：2007
• 卷：33
• 期：6
• 页码：821-828
• 全文大小：387 K

文摘

In this study, we present the visualization and clustering capabilities of self-organizing maps (SOM) for analyzing high-dimensional data. We used SOM because they implement an orderly mapping of a high-dimensional distribution onto a regular low-dimensional grid. We used surface texture parameters of volcanic ash that arose from different fragmentation mechanisms as input data. We found that SOM cluster 13-dimensional data more accurately than conventional statistical classifiers. The component planes constructed by SOM are more successful than statistical tests in determining the distinctive parameters.