Integrating XGBoost and Bayesian Maximum Entropy for 3D Probabilistic Lithology Modeling – A Case of Pingtung Plain, Taiwan

Huating Tseng

Presentation information

[E] Oral

A (Atmospheric and Hydrospheric Sciences ) » A-HW Hydrology & Water Environment

[A-HW32] Near Surface Investigation and Modeling for Groundwater Resources Assessment and Conservation

Mon. May 25, 2026 1:45 PM - 3:15 PM 106 (International Conference Hall, Makuhari Messe)

Chairperson:Lin Ying-Fan(Chung Yuan Christian University), Puntu Mahardika Jordi(National Central University), Huang Chun-Wei(National Yang Ming Chiao Tung University)

2:45 PM - 3:00 PM

[AHW32-05] Integrating XGBoost and Bayesian Maximum Entropy for 3D Probabilistic Lithology Modeling – A Case of Pingtung Plain, Taiwan

*Huating Tseng¹, Chia-Lun Wang¹, Yi Su², Hwa-Lung Yu¹ (1. National Taiwan University, 2. CECI Engineering Consultants, Inc., Taiwan)

Keywords:machine learning, geostatistical method, 3D hydrogeoglogical structure estimation

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