Bayesian approach for statistical modeling and forecasting of aftershock activities

Takahiro Omi

Presentation information

[J] Oral

S (Solid Earth Sciences ) » S-TT Technology & Techniques

[S-TT46] Seismic Big Data Analysis Based on the State-of-the-Art of Bayesian Statistics

Mon. May 27, 2019 1:45 PM - 3:15 PM A08 (TOKYO BAY MAKUHARI HALL)

convener:Hiromichi Nagao(Earthquake Research Institute, The University of Tokyo), Aitaro Kato(Earthquake Research Institute, the University of Tokyo), Takuto Maeda(Graduate School of Science and Technology, Hirosaki University), Keisuke Yano(The university of Tokyo), Chairperson:Nana Yoshimitsu(Earthquake Research Institute, The University of Tokyo), Takeru Matsuda(Graduate School of Information Science and Technology, The University of Tokyo)

2:30 PM - 2:45 PM

[STT46-04] Bayesian approach for statistical modeling and forecasting of aftershock activities

★Invited Papers

*Takahiro Omi¹ (1.Institue of Industrial Science, the University of Tokyo)

Keywords:aftershock activity, probabilistic forecasting, bayesian statistics

A large earthquake triggers a considerable number of aftershocks, which potentially cause additional damage in the affected area. It is therefore important to forecast aftershock activities as early as possible after a main shock. A basic method for forecasting aftershocks was proposed in 1989. However, for practical application of aftershock forecasting, we have to additionally consider (i) the missing of early aftershocks (ii) the forecast uncertainty. We consider such features by taking Bayesian statistical approach. In this talk, we briefly explain our forecasting method and demonstrate its utility.