The application of cluster analysis in geophysical data interpretation
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|Title:||The application of cluster analysis in geophysical data interpretation||Authors:||Song, Yu-Chen
O'Grady, Michael J.
O'Hare, G. M. P. (Greg M. P.)
|Permanent link:||http://hdl.handle.net/10197/1914||Date:||Mar-2010||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.||Funding Details:||Science Foundation Ireland||Type of material:||Journal Article||Publisher:||Springer||Journal:||Computational Geosciences||Volume:||14||Issue:||2||Start page:||263||End page:||271||Copyright (published version):||Springer, 2010||Keywords:||Cluster analysis; Geophysical data interpretation; Data mining||Subject LCSH:||Cluster analysis
|DOI:||10.1007/s10596-009-9150-1||Language:||en||Status of Item:||Peer reviewed|
|Appears in Collections:||CLARITY Research Collection|
Computer Science Research Collection
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