Probabilistic analysis of macroseismic fields: Iceland case study (Contributo in atti di convegno)

Type
Label
  • Probabilistic analysis of macroseismic fields: Iceland case study (Contributo in atti di convegno) (literal)
Anno
  • 2012-01-01T00:00:00+01:00 (literal)
Alternative label
  • Rotondi R, Brambilla C, Varini E, Sigbjörnsson R (2012)
    Probabilistic analysis of macroseismic fields: Iceland case study
    in 15th World Conference on Earthquake Engineering (15WCEE), Lisboa, Portugal, 2012, September 24-28
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Rotondi R, Brambilla C, Varini E, Sigbjörnsson R (literal)
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  • This study is co-financed by the EU-Civil Protection Financial Instrument, in the framework of the European project \"Urban disaster Prevention Strategies using MAcroseismic Fields and FAult Sources\" (UPStrat-MAFA - Num.230301/2011/613486/SUB/A5), DG ECHO Unit A5. (literal)
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  • Proceedings of the 15th World Conference on Earthquake Engineering (15WCEE) (literal)
Rivista
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  • 8 (literal)
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  • Consiglio Nazionale delle Ricerche, Istituto di Matematica Applicata e Tecnologie Informatiche, Italy. Consiglio Nazionale delle Ricerche, Istituto di Matematica Applicata e Tecnologie Informatiche, Italy. Consiglio Nazionale delle Ricerche, Istituto di Matematica Applicata e Tecnologie Informatiche, Italy. Earthquake Engineering Research Centre, Iceland. (literal)
Titolo
  • Probabilistic analysis of macroseismic fields: Iceland case study (literal)
Abstract
  • In this work our objectives are, first, to describe a probabilistic model aimed at forecasting macroseismic fields and, second, to present the results and findings obtained by applying the model to two of recent damaging earthquakes in the South Iceland Seismic Zone, namely, the earthquakes on 17 June, 2000 and 29 May, 2008, both of assessed epicentral intensity MMI X. The model considers the intensity decay as a random variable having a binomial probability distribution with parameter p, which is in its turn assumed to be a beta random variable. Estimation is carried out according to the Bayesian paradigm; on the basis of a learning set of macroseismic fields, we express our belief on the phenomenon by assigning prior distributions to the model parameters and we then update them with current data. The model has already been applied to Italian earthquakes, in particular, earthquakes occurring in the Mt. Etna volcanic environment. (literal)
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