Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/2097
Authors: Iervolino, I.* 
Convertito, V.* 
Giorgio, M.* 
Manfredi, G.* 
Zollo, A.* 
Title: Real-time risk analysis for hybrid earthquake early warning systems
Journal: Journal of Earthquake Engineering 
Series/Report no.: No. 6/Vol. 10, 2006
Publisher: Imperial College Press
Issue Date: 14-Jun-2006
DOI: 10.1080/13632460701258019
Keywords: Early warning
Hazard
Real-time
Risk
False alarm
Missed alarm
Subject Classification04. Solid Earth::04.06. Seismology::04.06.11. Seismic risk 
Abstract: Earthquake Early Warning Systems (EEWS), based on real-time prediction of ground motion or structural response measures, may play a role in reducing vulnerability and/or exposition of buildings and lifelines. In fact, recently seismologists developed efficient methods for rapid estimation of event features by means of limited information of the P-waves. Then, when an event is occurring, probabilistic distributions of magnitude and source-to-site distance are available and the prediction of the ground motion at the site, conditioned to the seismic network measures, may be performed in analogy with the Probabilistic Seismic Hazard Analysis (PSHA). Consequently the structural performance may be obtained by the Probabilistic Seismic Demand Analysis (PSDA), and used for real-time risk management purposes. However, such prediction is performed in very uncertain conditions which have to be taken into proper account to limit false and missed alarms. In the present study, real-time risk analysis for early warning purposes is discussed. The magnitude estimation is performed via the Bayesian approach, while the earthquake localization is based on the Voronoi cells. To test the procedure it was applied, by simulation, to the EEWS under development in the Campanian region (southern Italy). The results lead to the conclusion that the PSHA, conditioned to the EEWS, correctly predicts the hazard at the site and that the false/missed alarm probabilities may be controlled by set up of an appropriate decisional rule and alarm threshold.
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