Grade interpolation in orebody based on support vector regression

LI Juan; LI Cui-ping; LI Zhong-xue

doi:10.13374/j.issn1001-053x.2009.12.003

Volume 31 Issue 12

Aug. 2021

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LI Juan, LI Cui-ping, LI Zhong-xue. Grade interpolation in orebody based on support vector regression[J]. Chinese Journal of Engineering, 2009, 31(12): 1498-1502. doi: 10.13374/j.issn1001-053x.2009.12.003

Citation:

LI Juan, LI Cui-ping, LI Zhong-xue. Grade interpolation in orebody based on support vector regression[J]. Chinese Journal of Engineering, 2009, 31(12): 1498-1502. doi: 10.13374/j.issn1001-053x.2009.12.003

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Grade interpolation in orebody based on support vector regression

doi: 10.13374/j.issn1001-053x.2009.12.003

School of Civil and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China

Received Date: 2009-03-11
Available Online: 2021-08-09

Abstract

Abstract

The method of support vector regression (SVR) in combination with self organization feature mapping (SOFM) network was selected for grade interpolation in orebody, and was compared to the Thiessen polygons method, the distance power inverse ratio method and the Kriging method. The result shows that the prediction model of SVR is feasible and reliable for grade estimation.
- orebody,
- volume visualization,
- grade,
- support vector regression,
- space interpolation