Room B

PM-1

Thu. Oct 14, 2021 2:00 PM - 3:00 PM ROOM B (ROOM B)

chairperson:Hisahiko Kubo(NIED), Keisuke Yano(The Institute of Statistical Mathematics)

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2:00 PM - 2:15 PM

[S22-01] Construction of Convolutional Neural Network to Detect Deep Low-Frequency Tremors from Seismic Waveform Images

〇Ryosuke KANEKO^1,2, Hiromichi NAGAO^2,1, Shin-ichi ITO^2,1, Kazushige OBARA², Hiroshi TSURUOKA² (1.Graduate School of Information Science and Technology, The University of Tokyo, 2.Earthquake Research Institute, The University of Tokyo)

2:15 PM - 2:30 PM

[S22-02] Feature Extraction of Earthquake Time-Series Data by Dynamic Mode Decomposition

〇Ryota Kikuchi¹, Hisahiko Kubo² (1.Kyoto University, 2.National Research Institute for Earth Science and Disaster Resilience)

2:30 PM - 2:45 PM

[S22-03] Application of Bayesian Optimization to Black-Box Optimization Problem in Seismology: An Example of Centroid Moment Tensor Inversion

〇Hisahiko KUBO¹, Keisuke YOSHIDA², Takeshi KIMURA¹ (1.National Research Institute for Earth Science and Disaster Resilience, 2.Tohoku University)

2:45 PM - 3:00 PM

[S22-04] CMT Data Inversion Using Gaussian Processes

〇Tomohisa OKAZAKI¹, Yukitoshi FUKAHATA² (1.RIKEN Center for Advanced Intelligence Project, 2.Kyoto Univ. Disaster Prevention Research Institute)

Poster session (Oct. 14th)

P

Thu. Oct 14, 2021 3:30 PM - 5:00 PM ROOM P8 (ROOM P)

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3:30 PM - 5:00 PM

[S22P-01] Validation of Seismic Phase Picking Using Deep Learning Models Trained by Hakone Volcanic Earthquake Data

〇Ahyi KIM¹, Yuji Nakamura¹, Umi Hatakeyama¹, Hiroki Uematsu¹, Yohei Yukutake², Yuki Abe³ (1.Yokohama City University, 2.Earthquake Research Institute, the University of Tokyo, 3.Hot Springs Research Institute, Kanagawa)

3:30 PM - 5:00 PM

[S22P-02] Automatic reading of P-wave first motion amplitudes of acoustic emissions induced by hydraulic fracturing in laboratory using a deep learning technique

〇Makoto NAOI¹, Youqing CHEN¹, Rui TANAKA¹, Yutaro ARIMA² (1.Kyoto Univ., 2.JOGMEC)

3:30 PM - 5:00 PM

[S22P-03] Improvement of the Single Station Algorithm in Earthquake Early Warning Using Machine Learning Technique

〇Shunta NODA¹, Masato UKAI¹ (1.Railway Technical Research Institute)

Sessions

Special session » S22. Advances in Seismology using AI

PM-1

[S22-01] Construction of Convolutional Neural Network to Detect Deep Low-Frequency Tremors from Seismic Waveform Images

[S22-02] Feature Extraction of Earthquake Time-Series Data by Dynamic Mode Decomposition

[S22-03] Application of Bayesian Optimization to Black-Box Optimization Problem in Seismology: An Example of Centroid Moment Tensor Inversion

[S22-04] CMT Data Inversion Using Gaussian Processes

P

[S22P-01] Validation of Seismic Phase Picking Using Deep Learning Models Trained by Hakone Volcanic Earthquake Data

[S22P-02] Automatic reading of P-wave first motion amplitudes of acoustic emissions induced by hydraulic fracturing in laboratory using a deep learning technique

[S22P-03] Improvement of the Single Station Algorithm in Earthquake Early Warning Using Machine Learning Technique

Authentication