JpGU-AGU Joint Meeting 2026

Presentation information

[E] Poster

M (Multidisciplinary and Interdisciplinary) » M-GI General Geosciences, Information Geosciences & Simulations

[M-GI34] Data-driven approaches for weather and hydrological predictions

Mon. May 25, 2026 5:15 PM - 7:00 PM Poster Hall (Exhibition Hall 7&8, Makuhari Messe)

5:15 PM - 7:00 PM

[MGI34-P03] Estimating Hydraulic Conductivity of Fractured Rock Masses Using Deep Neural Networks: A Case Study from Taiwan

*Shih-Meng Hsu1, Cheng-Jun Zheng1 (1. National Taiwan Ocean University)

Keywords:Hydraulic conductivity, Fractured rock masses, Deep neural network , Geological indices, Hydrogeological indices