Three-Dimensional Broad Learning Gravity Data Inversion Using Single-Anomaly Training Samples

Three-Dimensional Broad Learning Gravity Data Inversion Using Single-Anomaly Training Samples

Gravity data inversion is of critical importance in geophysics, encompassing a range of applications, such as the exploration of geological resources, the identification of geological structures, and the detection of groundwater resources. This study proposes a three-dimensional (3D) machine learnin...

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Bibliographic Details
Main Authors: Guang-Jing Xu, Qiang Zu, Xiao-Hui Yang, Tao Tao, Peng Han, Qiang Luo, Sixu Han, Zhan-Xiang He
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Applied Sciences
Subjects:
gravity data inversion
machine learning
broad learning network
single-anomaly training samples
oil and gas resources
Online Access:https://www.mdpi.com/2076-3417/14/23/11409
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