Geological Literature Search (GEOLIS) (Geological Survey of Japan / AIST)

Deep Learning-based predicting of future frictional behavior via past physical parameters on experiment fault surface: A Transformer Architecture approach (abs.)

Authors=Tae-hoon UHMB, Takehiro Hirose, Yohei Hamada

Journal/Book_names=Abstracts, the 130th Annual Meeting of the Geological Society of Japan (online)

volume=130

pages=T1-O-1

Publish_year=2023

Publisher=Geological Society of Japan

Language_of_Text=EN

ISSN=21876665

DOI=10.14863/geosocabst.2023.0_8

ID=300038758

@id=https://gbank.gsj.jp/ld/resource/geolis/300038758