Application of Machine Learning Methods for Gravity Anomaly Prediction

Application of Machine Learning Methods for Gravity Anomaly Prediction

Gravity anomalies play critical roles in geological analysis, geodynamic monitoring, and precise geoid modeling. Obtaining accurate gravity data is challenging, particularly in inaccessible or sparsely covered regions. This study evaluates machine learning (ML) methods—Support Vector Regression (SVR...

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Bibliographic Details
Main Authors: Katima Zhanakulova, Bakhberde Adebiyet, Elmira Orynbassarova, Ainur Yerzhankyzy, Khaini-Kamal Kassymkanova, Roza Abdykalykova, Maksat Zakariya
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Geosciences
Subjects:
gravity data prediction
machine learning
support vector regression
ensembles of trees
Gaussian process regression
Online Access:https://www.mdpi.com/2076-3263/15/5/175
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