Session Details
[S21P]PM-P
Wed. Nov 1, 2023 5:00 PM - 6:30 PM JST
Wed. Nov 1, 2023 8:00 AM - 9:30 AM UTC
Wed. Nov 1, 2023 8:00 AM - 9:30 AM UTC
Room P3 (F205 and 6 side foyer) Hall Annex
[S21P-01]On the effects of time width used to count interval maximum amplitude of a seismogram on the extreme value analysis
*Kaoru SAWAZAKI1 (1. National Research Institute for Earth Science and Disaster Resilience)
[S21P-02]AE Catalog development by a deep hashing method and network correlation analysis
*Makoto NAOI1, Shiro HIRANO2, Youqing CHEN1 (1. Kyoto University, 2. Ritsumeikan University)
[S21P-03]Attempt to Predict Response Spectra from Fourier Spectra Using Machine Learning
*Yuki Kurata1, Hiroaki Matsukawa1, Hiroto Tanaka1, Yasuhiro Matsumoto1, Mika Takekoshi1, Takachika Yagi1, Ryota Kiuchi1, Yuta Taki1 (1. KOZO KEIKAKU ENGINEERING Inc.)
[S21P-04]Predicting the probability of seismic motion exceedance based on short-term earthquake probability information after a large earthquake
*Hisahiko KUBO1, Katsuhiko SHIOMI1 (1. National Research Institute for Earth Science and Disaster Resilience)
[S21P-05]Comprehensive detection of later phase in S coda throughout the inland Japanese archipelago with deep learning
*Yuta AMEZAWA1, Takahiko Uchide1, Takahiro Shiina1, Jun Ogata2, Satoru Fukayama2, Hiroki Kuroda3 (1. Geological Survey of Japan, National Institute of Advanced Industrial Science and Technology, 2. Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology , 3. Department of Information and Management Systems Engineering, Nagaoka University of Technology)
[S21P-06]Extraction of deep tectonic tremor waveforms using deep learning: Application to Hi-net stations in the Nankai subduction zone
*Yuya Jinde1, Amane Sugii1, Yoshihiro Hiramatsu1 (1. Kanazawa University)
[S21P-07]You Only Search Once: An alternative framework to detect slow earthquakes.
*GERARDO MANUEL MENDO PEREZ1, HIROMICHI NAGAO1 (1. Earthquake Research Institute, The University of Tokyo)
[S21P-08]Which is more suitable for polarity determination using deep learning, time series data or image data?
*Shinya KATOH1, Yoshihisa IIO2, Hiroshi KATAO2, Masayo SAWADA2, Kazuhide TOMISAKA2 (1. Earthquake Research Institute,The University of Tokyo, 2. Disaster Prevention Research Institute Kyoto University)
[S21P-09]Fast Smoothing Method for Spatiotemporal Data and Its Application to Seismic Wavefield Reconstruction
*Yoshikazu Terada1,2, Hidetoshi Matsui3, Hiromichi Nagao4 (1. Osaka Univ., 2. RIKEN, 3. Shiga Univ., 4. Earthquake Research Institute, Univ. of Tokyo)
[S21P-10]Hypocenter-based Visualization of Multiscale Earthquake Faults:
Application to Crustal Earthquakes in Japan Islands
*Yasunori SAWAKI1, Yoshihiro SATO2,3, Takahiko UCHIDE1, Haruo HORIKAWA1, Takahiro SHIINA1, Yuta AMEZAWA1 (1. Geological Survey of Japan, AIST, 2. Tokyo City University, 3. Artificial Intelligence Research Center, AIST)
[S21P-11]Construction of a high-performance volcanic earthquake phase detection model using deep learning and examination of its transfer learning
*Yuji Nakamura1,2, Ahyi Kim1, Yohei Yukutake3, Yuki Abe4 (1. Yokohama City University, 2. activecore, Inc., 3. Earthquake Research Institute, University of Tokyo, 4. Hot Springs Research Institute of Kanagawa Prefecture)
[S21P-12]Machine-learning model of GNSS displacement rate estimation using seismic waveforms in western Shikoku
*Kazuki OHTAKE1, Aitaro KATO1, Yutaro OKADA2, Takuya NISHIMURA3 (1. Earthquake Research Institute, The University of Tokyo, 2. Graduate School of Science, Kyoto University, 3. Disaster Prevention Research Institute, Kyoto University)
[S21P-13]Evaluation of GNSS-A positioning accuracy using a simple numerical model and the PyMC library
*Yuto NAKAMURA1, Tadashi Ishikawa1, Yusuke Yokota2, Shun-ichi Watanabe1, Koya Nagae1 (1. Hydrographic and Oceanographic Department, Japan Coast Guard, 2. Institute of Industrial Science, University of Tokyo)
[S21P-14]Acoustic waveform analysis for GNSS-Acoustic observation using Machine Learning
*Naoki Kurosu1, Motoyuki Kido2 (1. Graduate School of Science, Tohoku University, 2. International Research Institute for Disaster Science, Tohoku University)
[S21P-15]Development of a Seismic Phase Pick System using Machine Learning for a Citizen Seismic Network
*Yukino Yazaki1, Yuji Nakamura1, Hiroki Uematsu1,2, Ahyi Kim1, Masami Yamasaki1 (1. Yokohama City University, 2. National Institute of Informatics)