[S-CG55] Driving Solid Earth Science through Machine Learning

Sun. May 21, 2023 3:30 PM - 4:45 PM 302 (International Conference Hall, Makuhari Messe)

convener:Hisahiko Kubo(National Research Institute for Earth Science and Disaster Resilience), Yuki Kodera(Meteorological Research Institute, Japan Meteorological Agency), Makoto Naoi(Kyoto University), Keisuke Yano(The Institute of Statistical Mathematics), Chairperson:Ahyi KIM(Graduate School of Nanobioscience, Yokohama City University), Hisahiko Kubo(National Research Institute for Earth Science and Disaster Resilience)

Machine learning (ML) has brought innovations and remarkable results in various science fields including solid earth science. This session provides an opportunity to inspire each other for future developments by bringing studies of ML applications in various fields including solid earth science. We invite a wide range of presentations on ML and related research, from the budding to the more advanced.

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3:30 PM - 4:00 PM

[SCG55-11] Solar Flare Prediction and Space Weather Forecasting using Machine Learning

★Invited Papers

*Naoto Nishizuka¹ (1.National Institute of Information and Communications Technology)

4:00 PM - 4:15 PM

[SCG55-12] Prediction of Tsunami Flow Depth Distribution of Nankai Trough Earthquake Tsunami Using Machine Learning and Seafloor Water Pressure Data

*Masato Kamiya¹, Toshitaka Baba² (1.Graduate School of Sciences and Technology for Innovation, Tokushima University, 2.Graduate School of Science and Technology, Tokushima University)

4:15 PM - 4:30 PM

[SCG55-13] A forecast of long-period ground motions by using a convolutional neural network

*Daiki TAYA¹, Takashi Furumura¹ (1.Earthquake Research Institute, the University of Tokyo)

4:30 PM - 4:45 PM

[SCG55-14] Construction of a real-time seismic intensity prediction model using deep learning: evaluation of data augmentation with synthetic data

*Ahyi KIM¹, Momoko NAKAMURA¹, Anju OHTA¹, Yukino YAZAKI¹, Hisahiko KUBO² (1.Yokohama City University, 2.National Research Institute for Earth Science and Disaster Resilience)

Session information