Danian Huang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Danian Huang has a total of 14 co-authors. Here are the top co-authors by number of shared publications:
- Boyuan Zhu
Griffith University 170 Kessels Road, Nathan, Brisbane, Australia
1 shared publication - Dailei Zhang
Chinese Academy of Geological Sciences, Beijing, China
1 shared publication - Jian Jiao
Jilin University Changchun, China
1 shared publication - Junwei Lu
Griffith University
1 shared publication Mei-Xia Geng
Jilin University
1 shared publicationQing-Lu Yu
Sinopec Geophysical Research Institute
1 shared publication
Latest Publications
- Open Access
- 1 December 2016
- Published by Taylor & Francis in ASEG Extended Abstracts
- Vol. 2016 (1) , 1-3
Aeromagnetic compensation with partial least square regression
Magnetic exploration plays a significant role in regional geological investigation and detection of underground geological bodies with magnetic anomaly. At the moment, aeromagnetic survey is widely applied for its high efficiency, low cost and less subject to terrain restrict. Magnetic compensation is a key step in pre-processing survey data and several methods have been used. In this paper, we would use partial least square method to complete aeromagnetic compensation. Partial least square regression is frequently used to find the fundamental relations between two matrices. It combines linear regression analysis, canonical correlation analysis and principal components analysis. It can be applied into data with multicollinearity among independent variables and the number of variables is larger than that of observations. Before compensation, we should have several pre-processing steps such as parallax correction, diurnal variations correction, geomagnetic field correction and high-frequency noise removal. This will provide us magnetic data with higher quality and make compensation process more accurate. We set synthetic aeromagnetic data with interference of aircraft’s maneuvers and used partial least square method to do compensation. From the results of simulation, we can see that the interference signal is reduced to a low degree and satisfied compensation effect is obtained. Partial least square regression is a stable and effective method in the application of aeromagnetic compensation.
- 1 December 2016
- Published by Taylor & Francis in ASEG Extended Abstracts
- Vol. 2016 (1) , 1-3
Open AccessAeromagnetic compensation with partial least square regression
Magnetic exploration plays a significant role in regional geological investigation and detection of underground geological bodies with magnetic anomaly. At the moment, aeromagnetic survey is widely applied for its high efficiency, low cost and less subject to terrain restrict. Magnetic compensation is a key step in pre-processing survey data and several methods have been used. In this paper, we would use partial least square method to complete aeromagnetic compensation. Partial least square regression is frequently used to find the fundamental relations between two matrices. It combines linear regression analysis, canonical correlation analysis and principal components analysis. It can be applied into data with multicollinearity among independent variables and the number of variables is larger than that of observations. Before compensation, we should have several pre-processing steps such as parallax correction, diurnal variations correction, geomagnetic field correction and high-frequency noise removal. This will provide us magnetic data with higher quality and make compensation process more accurate. We set synthetic aeromagnetic data with interference of aircraft’s maneuvers and used partial least square method to do compensation. From the results of simulation, we can see that the interference signal is reduced to a low degree and satisfied compensation effect is obtained. Partial least square regression is a stable and effective method in the application of aeromagnetic compensation.
- 12 April 2016
- Published by Springer Nature in Acta Geodaetica et Geophysica
- Vol. 52 (3) , 317-329
Total horizontal derivatives of potential field three-dimensional structure tensor and their application to detect source edges
- 12 April 2016
- Published by Springer Nature in Acta Geodaetica et Geophysica
- Vol. 52 (3) , 317-329
Total horizontal derivatives of potential field three-dimensional structure tensor and their application to detect source edges
- 1 September 2015
- Published by Springer Nature in Applied Geophysics
- Vol. 12 (3) , 292-302
Full tensor gravity gradiometry data inversion: Performance analysis of parallel computing algorithms
- 1 September 2015
- Published by Springer Nature in Applied Geophysics
- Vol. 12 (3) , 292-302
Full tensor gravity gradiometry data inversion: Performance analysis of parallel computing algorithms
- 29 July 2015
- Published by Springer Nature in Acta Geodaetica et Geophysica
- Vol. 51 (3) , 435-449
Taylor iteration downward continuation method for gravity gradient tensor data
- 29 July 2015
- Published by Springer Nature in Acta Geodaetica et Geophysica
- Vol. 51 (3) , 435-449
Taylor iteration downward continuation method for gravity gradient tensor data
- 8 July 2015
- Published by Springer Nature in Pure and Applied Geophysics
- Vol. 173 (2) , 509-523
Fast Density Inversion Solution for Full Tensor Gravity Gradiometry Data
- 8 July 2015
- Published by Springer Nature in Pure and Applied Geophysics
- Vol. 173 (2) , 509-523
Fast Density Inversion Solution for Full Tensor Gravity Gradiometry Data
- 1 September 2013
- Published by Springer Nature in Applied Geophysics
- Vol. 10 (3) , 241-250
Noise filtering of full-gravity gradient tensor data
- 1 September 2013
- Published by Springer Nature in Applied Geophysics
- Vol. 10 (3) , 241-250
Noise filtering of full-gravity gradient tensor data