On the Finding Process of Volcano-Domain Ontology Components Using Self-Organizing Maps

  • Authors:

  • J. R. Pulido;M. A. Aréchiga;E. M. Michel;G. Reyes;V. Zobin

  • Affiliations:

  • Faculty of Telematics, University of Colima, México;Faculty of Telematics, University of Colima, México;Faculty of Telematics, University of Colima, México;Volcanic observatory (RESCO), University of Colima, México;Volcanic observatory (RESCO), University of Colima, México

  • Venue:
  • WSOM '09 Proceedings of the 7th International Workshop on Advances in Self-Organizing Maps
  • Year:
  • 2009

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Abstract

Monitoring volcanic activity is a task that requires people from a number of disciplines. Infrastructure, on the other hand , has been built all over the world to keep track of these living earth entities, ie volcanoes. In this paper we present an approach that merges a number of computational tools and that may be incorporated to existing ones to predict important volcanic events. It mainly consists of applying artificial learning, ontology, and software agents for the analysis, organization, and use of volcanic-domain data for the communities of people, living nearby volcanoes, benefit. This proposal allows domain experts to have a view of the knowledge contained in and that can be extracted from the Volcanic-Domain Digital Archives (VDDA). Specific-domain knowledge components with further processing, and by embedding them into the digital archive itself, can be shared with and manipulated by software agents. In this first study, we deal with the issue of applying Self-Organizing Maps (SOM), to volcano-domain signals originated by the activity of the Volcano of Colima, Mexico. By applying this algorithm we have generated clusters of volcanic activity and can readily identify families of important events.