How to help seismic analysts to verify the French seismic bulletin?

Authors:
David Mercier;Pierre Gaillard;Michaël Aupetit;Carole Maillard;Robert Quach;Jean-Denis Muller
Affiliations:
CEA DAM, Analysis, Surveillance, Environment Department, BP 12, F-91680 Bruyères-Le-Chítel, France;CEA DAM, Analysis, Surveillance, Environment Department, BP 12, F-91680 Bruyères-Le-Chítel, France;CEA DAM, Analysis, Surveillance, Environment Department, BP 12, F-91680 Bruyères-Le-Chítel, France;CEA DAM, Analysis, Surveillance, Environment Department, BP 12, F-91680 Bruyères-Le-Chítel, France;CEA DAM, Analysis, Surveillance, Environment Department, BP 12, F-91680 Bruyères-Le-Chítel, France;CEA DAM, Analysis, Surveillance, Environment Department, BP 12, F-91680 Bruyères-Le-Chítel, France
Venue:
Engineering Applications of Artificial Intelligence
Year:
2006

Citing 3
Cited 0

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Abstract

In this paper, classifiers based on Multi-Layer Perceptrons and Support Vector Machines are used in order to classify seismic events that occurred in metropolitan France. The results are exploited in the software RAMSES to help the seismic analysts to conduct efficiently the revision of the weekly French seismic bulletin. With 96.5% of good classification, and less than 7% of the events emphasized for verification, RAMSES strikingly improves the speed of the revision.