dr. Masumi Yamada, Earthquake Hazards Division, DPRI, Kyoto University - ore 11.00 - aula 1G09 - Dipartimento di Fisica "Ettore Pancini", Complesso Universitario di Monte S.Angelo - Via Cintiia, Napoli.
ABSTRACT
Current earthquake early warning (EEW) systems lack the ability to appropriately handle multiple concurrent earthquakes, which led to many false alarms during the 2011 Tohoku earthquake sequence in Japan. We uses a Bayesian probabilistic approach to handle multiple concurrent events for EEW. We improved the model to estimate earthquake parameters, i.e., hypocenter location, origin time, magnitude and seismic intensity, by using extra information which is not used before. Then, the sequential Monte Calro method is used to estimate the earthquake parameters. A real data example based on two months data (March 9 to April 30, 2011) around the time of the 2011 Tohoku earthquake is studied to verify the proposed algorithm. Our algorithm results in over 90% improvement compared to the existing EEW system.