Assessing macroseismic data reliability through rough set theory: the case of rapolla (basilicata, southern italy)

Authors:
Fabrizio Gizzi;Nicola Masini;Maria Rosaria Potenza;Cinzia Zotta;Lucia Tilio;Maria Danese;Beniamino Murgante
Affiliations:
Archaeological and monumental heritage institute, National Research Council, Tito Scalo, (PZ), Italy;Archaeological and monumental heritage institute, National Research Council, Tito Scalo, (PZ), Italy;Archaeological and monumental heritage institute, National Research Council, Tito Scalo, (PZ), Italy;Archaeological and monumental heritage institute, National Research Council, Tito Scalo, (PZ), Italy;Laboratory of Urban and Territorial Systems, University of Basilicata, Potenza, Italy;Laboratory of Urban and Territorial Systems, University of Basilicata, Potenza, Italy;Laboratory of Urban and Territorial Systems, University of Basilicata, Potenza, Italy
Venue:
ICCSA'10 Proceedings of the 2010 international conference on Computational Science and Its Applications - Volume Part I
Year:
2010

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ROSE - Software Implementation of the Rough Set Theory

RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing

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Abstract

This paper deals with the analysis of the reliability of information concerning damages caused to buildings by earthquakes. This research was started after analyzing a huge amount of written sources drawn up after 1930 Irpinia (southern Italy) earthquake. The analysis led to delineate damage ‘scenarios', useful in trying to mitigate seismic risk for most affected towns. Once analyzed the effects induced by the quake, it was suitable to assess the reliability of the retrieved information. To face up this subject the town of Rapolla (PZ, Basilicata, southern Italy) was chosen as test bed. The whole data set, concerning administrative-technical aspects of 1930 earthquake, was analyzed through Rough Set Approach, a non-parametric statistic methodology. Considering that the town of Rapolla represents a piece of the entire corpus of information available for 1930 earthquake, this paper shows preliminary insights about the subject.