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http://hdl.handle.net/2122/10689
Authors: | Cannavò, Flavio* Cannata, Andrea* Cassisi, Carmelo* Di Grazia, Giuseppe* Montalto, Placido* Prestifilippo, Michele* Privitera, Eugenio* Coltelli, Mauro* Gambino, Salvatore* |
Title: | A multivariate probabilistic graphical model for real-time volcano monitoring on Mount Etna | Journal: | Journal of Geophysical Research: Solid Earth | Series/Report no.: | /122 (2017) | Issue Date: | 20-Apr-2017 | DOI: | 10.1002/2016JB013512 | Abstract: | Real-time assessment of the state of a volcano plays a key role for civil protection purposes. Unfortunately, because of the coupling of highly nonlinear and partially known complex volcanic processes, and the intrinsic uncertainties in measured parameters, the state of a volcano needs to be expressed in probabilistic terms, thus making any rapid assessment sometimes impractical. With the aim of aiding on-duty personnel in volcano-monitoring roles, we present an expert system approach to automatically estimate the ongoing state of a volcano from all available measurements. The system consists of a probabilistic model that encodes the conditional dependencies between measurements and volcanic states in a directed acyclic graph and renders an estimation of the probability distribution of the feasible volcanic states.We test the model with Mount Etna (Italy) as a case study by considering a long record of multivariate data. Results indicate that the proposed model is effective for early warning and has considerable potential for decision-making purposes. |
Appears in Collections: | Article published / in press |
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Cannav-_et_al-2017-Journal_of_Geophysical_Research-_Solid_Earth.pdf | 2.81 MB | Adobe PDF | View/Open |
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