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Publicação
A support vector machine seismic detector for early-warning applications
Orientador(es)
Resumo(s)
This paper extends a Support Vector Machine (SVM) approach for the detection of seismic events, at the level of a seismic station. In previous works, it was shown that this approach produced excellent results, in terms of the Recall and Specificity measures, whether applied off-line or in a continuous scheme. The drawback was the time taken for achieving the detection, too large to be applied in a Early-Warning System (EWS). This paper shows that, by using alternative input features, a similar performance can be obtained, with a significant reduction in detection time. Additionally, it is experimentally proved that, whether off-line or in continuous operation, the best results are obtained when the SVM detector is trained with data originated from the respective seismic station.
Descrição
Palavras-chave
Smart systems Actuators and distributed systems Computational intelligence methods in modeling Systems identification and control
Contexto Educativo
Citação
Ruano, A. E.; Madureira, G.; Barros, O.; Khosravani, H.R.; Ruano, M.G.; Ferreira, P.M.A Support Vector Machine Seismic Detector for Early-Warning Applications, Trabalho apresentado em Intelligent Control and Automation Science, In 3rd IFAC International Conference on Intelligent Control and Automation Science (2013), Chengdu, 2013.
Editora
Elsevier, IFAC