Japan Geoscience Union Meeting 2018

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[JJ] Oral

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

[M-GI27] Data-driven geosciences

Wed. May 23, 2018 10:45 AM - 12:15 PM 301A (3F International Conference Hall, Makuhari Messe)

convener:Tatsu Kuwatani(Japan Agency for Marine-Earth Science and Technology), Hiromichi Nagao(Earthquake Research Institute, The University of Tokyo), Takane Hori(独立行政法人海洋研究開発機構・地震津波海域観測研究開発センター), Chairperson:Kuwatani Tatsu(JAMSTEC), Matumura Taroujirou

11:30 AM - 11:45 AM

[MGI27-16] Spatiotemporal data analysis with dynamic mode decomposition

★Invited Papers

*Yoshinobu Kawahara1 (1.Osaka University)

Keywords:Data-driven science, Machine learning

Dynamic mode decomposition (DMD) is a method for estimating a modal representation of the underlying dynamics from spatiotemporal data, and has been recently applied to a variety of scientific fields. In this talk, I give a brief review on the principles of DMD, and describe the recent development of the related methods with several applications to scientific data.