Username/Email： Password：
 
网站首页 Home Bulletins Highlights Books Meetings Frontline Messages Search Pictures Aboutus
Journal: Bulletin of Seismological Society of America  2018 No.4  Share to Sinaweibo  Share to QQweibo  Share to Facebook  Share to Twitter    clicks:186   
Title:
Rapid Earthquake Discrimination for Earthquake Early Warning: A Bayesian Probabilistic Approach Using Three‐Component Single‐Station Waveforms and Seismicity Forecast
Author: Lucy Yin ; Jennifer Andrews ; Thomas Heaton
Adress: Department of Civil and Mechanical Engineering, California Institute of Technology, 1200 East California Boulevard, Pasadena, California 91106, lyin@caltech.edu
Abstract: The utility of Earthquake Early Warning (EEW) relies on the robust and rapid classification of near‐site earthquake source signals from noise and teleseismic arrivals. To achieve this goal, we propose using the three‐component acceleration and velocity waveform data and epidemic‐type aftershock sequence (ETAS) seismicity forecast information in parallel, which will produce a posterior prediction by combining the predictions from the heterogeneous sources using a Bayesian probabilistic approach. We collected 2481 three‐component strong‐motion records for training and testing. The rapid prediction is available as quickly as 0.5 s after the trigger at a single station and updates every 0.5 s up to 3.0 s, achieving a precision rate of 94.7% at the first prediction with the classification accuracy increasing with time. The leave‐one‐out cross‐validation method also demonstrates confidence of robust performance for future earthquake signal detections. We compared the method with the 

Comment:
Write a comment about this article

To avoid abuse of the message board, all messages will be checked before publishing.
 

Phone：+86-028-84073851
Address：College of Geophysics, Chengdu University of Technology
            No.1, Erxianqiao East 3rd Road, Chenghua District, Chengdu, Sichuan, China 610059
             You are the No.0 visitor.