Three-Dimensional Mineral Prospectivity Mapping by a Gradient Boosting-Based Integrated Learning Method with Data Representation Adaptability

Mingjing Fan; keyan Xiao; Li Sun; Yang Xu

doi:https://doi.org/10.5194/egusphere-egu26-8798

[Back] [Session ERE4.1]

EGU26-8798, updated on 14 Mar 2026

https://doi.org/10.5194/egusphere-egu26-8798

EGU General Assembly 2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Three-Dimensional Mineral Prospectivity Mapping by a Gradient Boosting-Based Integrated Learning Method with Data Representation Adaptability

Mingjing Fan¹, keyan Xiao², Li Sun², and Yang Xu³

Mingjing Fan et al.

¹China Geological Survey, Tianjin Center,China Geological Survey, China (672284819@qq.com)
²SinoProbe Laboratory, Institute of Mineral Resources, Chinese Academy of Geological Sciences,
³China University of Geosciences (Beijing)

How to cite: Fan, M., Xiao, K., Sun, L., and Xu, Y.: Three-Dimensional Mineral Prospectivity Mapping by a Gradient Boosting-Based Integrated Learning Method with Data Representation Adaptability, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8798, https://doi.org/10.5194/egusphere-egu26-8798, 2026.

This abstract has been withdrawn after no-show on 11 Aug 2026.