Geological Literature
Deep Learning-based predicting of future frictional behavior via past physical parameters on experiment fault surface: A Transformer Architecture approach (abs.)
Tae-hoon UHMB, Takehiro Hirose, Yohei Hamada
| item | description |
|---|---|
| Title | 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 |
| Data name | Abstracts, the 130th Annual Meeting of the Geological Society of Japan (online) |
| Volume | 130 |
| Page | T1-O-1 |
| Year | 2023 |
| Publisher | Geological Society of Japan |
| Language | EN |
| ISSN | 21876665 |
| GEOLIS URL | https://darc.gsj.jp/archives/detail?cls=geolis&pkey=300038758 |
| DOI | 10.14863/geosocabst.2023.0_8 |
| @id | https://gbank.gsj.jp/ld/resource/geolis/300038758 |