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| Keywords | |
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support vector machine |
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K-means clustering |
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combination anomaly |
| Authors | |
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ZHANG Zhen-Ting-1 |
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WANG Zhong-Wen-1 |
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2 |
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MA Yan-Ying-1 |
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2 |
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WANG Miao-1 |
| PubMed | |
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Article by Zhang, Z. T. 1 |
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Article by Wang, Z. W. 1 |
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Article by 2 |
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Article by Ma, Y. Y. 1 |
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Article by 2 |
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Article by Wang, M. 1 |
Application of support vector machine in geochemical exploration
ZHANG Zhen-Ting-1, WANG Zhong-Wen-1, 2, MA Yan-Ying-1, 2, WANG Miao-1
1. Research Institute of Synthetic Information Mineral Resources Prediction, Jilin University, Changchun 130026, China; 2. Jilin Teachers Institute of Engineering and Technology, Changchun 130052, China
The combination of K-means clustering and v -SVM gives a improved classified method which built a classified model with strong ability to distinguish based on the correlation. The model is applied in the exploration geochemical research in some places of Inner Mongolia, it which made clear in the similarity among the studied elements, and established v -SVM classifier to realize the delineation of combination anomaly.