Regional Geomagnetic Map Construction based on Support Vector Machine Residual Kriging

被引：0

作者：

Liu, Tong ^{[1
,2
]}

Li, Xingyu ^{[1
,2
]}

Fu, Mengyin ^{[1
,2
,3
]}

Liang, Zhaoxiang ^{[1
]}

机构：

[1] Beijing Inst Technol, Beijing 100081, Peoples R China

[2] Key Lab Complex Syst Intelligent Control & Decis, Beijing 100081, Peoples R China

[3] Nanjing Univ Sci & Technol, Nanjing 210094, Peoples R China

来源：

PROCEEDINGS OF THE 39TH CHINESE CONTROL CONFERENCE | 2020年

关键词：

Regional Geomagnetic Map; Kriging; Support Vector Machine;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Regional geomagnetic maps are widely used in geomagnetic navigation and magnetic anomaly detection. However, the complexity of geomagnetic spatial trend changes and the spatial sparseness of the geomagnetic data affect the accuracy of regional geomagnetic map construction. In order to improve the accuracy of regional geomagnetic maps, this paper proposes the Support Vector Machine Residual Kriging method (SVMRKriging). First, Support Vector Machine (SVM) is used to tit the geomagnetic trend changes, then the residual component is interpolated by ordinary Kriging, and finally these two parts are added to construct a regional geomagnetic map. Experiments were performed using geomagnetic grid data and aeromagnetic data. The experiment results show that SVMRKriging method can improve the accuracy of regional geomagnetic maps with geomagnetic trend changes.

引用

页码：3500 / 3504

页数：5

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