Data-Driven Science Using Sparse Modeling for Immediate Tsunami Height Prediction

Yasuhiko Igarashi

Presentation information

[J] Oral

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

[M-GI34] Data-driven geosciences

Sun. May 22, 2022 3:30 PM - 5:00 PM 301A (International Conference Hall, Makuhari Messe)

convener:Tatsu Kuwatani(Japan Agency for Marine-Earth Science and Technology), convener:Hiromichi Nagao(Earthquake Research Institute, The University of Tokyo), Kenta Ueki(Japan Agency for Marine-Earth Science and Technology), convener:Shin-ichi Ito(The University of Tokyo), Chairperson:Kenta Ueki(Japan Agency for Marine-Earth Science and Technology), Tatsu Kuwatani(Japan Agency for Marine-Earth Science and Technology), Shin-ichi Ito(The University of Tokyo), Hiromichi Nagao(Earthquake Research Institute, The University of Tokyo)

4:45 PM - 5:00 PM

[MGI34-06] Data-Driven Science Using Sparse Modeling for Immediate Tsunami Height Prediction

★Invited Papers

*Yasuhiko Igarashi¹ (1.University of Tsukuba)

Keywords:sparse modeling, Immediate Tsunami Height Prediction, Gaussian process

In the field of natural science, data-driven approach using various machine learning methods has been vigorously developed in recent years. Large-scale spatio-temporal data is becoming a target, and it is necessary to perform analysis while extracting a small number of important features. In this presentation, the development of data-driven science using sparse modeling for immediate prediction of tsunami height will be described, and the practice of data-driven science using sparse modeling will be discussed.