The event bush as a semantic-based numerical approach to natural hazard assessment (exemplified by volcanology)

  • Authors:

  • C. A. Pshenichny;S. I. Nikolenko;R. Carniel;P. A. Vaganov;Z. V. Khrabrykh;V. P. Moukhachov;V. L. Akimova-Shterkhun;A. A. Rezyapkin

  • Affiliations:

  • Geological Mapping Division, VNII Okeangeologia, Angliisky Prospect, 1, St. Petersburg 190121, Russian Federation and Levinson-Lessing Earthcrust Research Institute, St. Petersburg State Universit ...;St. Petersburg Department of the Steklov Mathematical Institute, Naberezhnaya Reki Fontanki, 27, St. Petersburg, Russian Federation;Dip. Georisorse e Territorio, Universití di Udine, Via Cotonificio 114, I-33100 Udine, Italy;Ecological Geology Department, Faculty of Geology, St. Petersburg State University, Universitetskaya Naberezhnaya, 7/9, St. Petersburg 199034, Russian Federation;Laboratory "Magma and Volcanoes", University of Blaise Pascal, 24 Avenue des Landais 63177-AUBIERE Cedex, Clermont-Ferrand, France;Logic Department, Faculty of Philosophy, St. Petersburg State University, Mendeleevskaya Liniya, 5, St. Petersburg 199034, Russian Federation;Karpinsky All-Russia Geological Research Institute (VSEGEI), Sredny Prospect, 74, St. Petersburg 191126, Russian Federation;Karpinsky All-Russia Geological Research Institute (VSEGEI), Sredny Prospect, 74, St. Petersburg 191126, Russian Federation

  • Venue:
  • Computers & Geosciences
  • Year:
  • 2009

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Abstract

The event bush is a new formalism for organizing knowledge in various fields of geoscience, particularly suitable for hazard assessment purposes. Acting as an intermediary between expert knowledge and the well-established field of Bayesian belief networks, the event bush allows at the same time a variety of other applications, linking geoscientific knowledge to the field of artificial intelligence and uniting probabilistic, deterministic, and fuzzy approaches. In this paper, we present basic principles, mathematical formulation, guidelines for application, and examples, including the connection with Bayesian belief networks. Further development of the method will include spatial and temporal modelling, implementation in mapping in GIS medium, formalization by means of predicate logic, definition of variable states in BBNs by membership functions based on the event bush semantics, and other applications.