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Please use this identifier to cite or link to this item:
http://hdl.handle.net/10197/1914
This item was peer reviewed 
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| Title: | The application of cluster analysis in geophysical data interpretation |
| Author: | Song, Yu-Chen
Meng, Hai-Dong
O'Grady, Michael J.
O'Hare, G. M. P. (Greg M. P.) |
| Date: | Mar-2010 |
| Full citation: | Computational Geosciences, 14 (2): 263-271 |
| Publisher: | Springer |
| Type of material: | Journal Article |
| Abstract: | A clustering algorithm which is based on density and adaptive density-reachable is developed and presented for arbitrary data point distributions in some real world applications, especially in geophysical data interpretation. Through comparisons of the new algorithm and other algorithms, it is shown that the new algorithm can reduce the dependency of domain knowledge and the sensitivity of abnormal data points, that it can improve the effectiveness of clustering results in which data are distributed in different shapes and different density, and that it can get a better clustering efficiency. The application of the new clustering algorithm demonstrates that data mining techniques can be used in geophysical data interpretation and can get meaningful and useful results, and that the new clustering algorithm can be used in other real world applications. |
| Web link to reference this item: | http://hdl.handle.net/10197/1914 |
| ISSN: | 1420-0597 (Print)
1573-1499 (Online) |
| DOI: | 10.1007/s10596-009-9150-1 |
| Keywords: | Cluster analysis; Geophysical data interpretation; Data mining; |
| Subject Heading: | Cluster analysis; Geophysics--Data processing; Data mining; |
| Status of Item: | Peer reviewed |
| Availability: | Full text available |
| Appears in Collections: | CSI Research Collection
CLARITY Research Collection
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