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EnglishReal-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.
| Titolo: | A multivariate probabilistic graphical model for real-time volcano monitoring on Mount Etna |
| Autori interni: | CANNATA, ANDREA (Secondo) |
| Data di pubblicazione: | 2017 |
| Rivista: | |
| Handle: | http://hdl.handle.net/20.500.11769/363233 |
| Appare nelle tipologie: | 1.1 Articolo in rivista |
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http://hdl.handle.net/20.500.11769/363233
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