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.
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References
Gizzi, F.T.: To what degree can historical seismicity records assist in seismic microzonation? Engineering Geology 87, 1–12 (2006)
Gizzi, F.T., Masini, N.: Damage scenario of the earthquake on 23 July 1930 in Melfi: the contribution of the technical documentation. Annals of Geophysics 47(5), 1641–1665 (2004)
Gizzi, F.T., Masini, N.: Historical damage pattern and differential seismic effects in a town with ground cavities: A case study from Southern Italy. Engineering Geology 88, 41–58 (2006)
Pawlak, Z.: Rough set approach to knowledge-based decision support. European Journal of Operational Research 99, 48–57 (1997)
Pawlak, Z.: Rough set theory and its applications to data analysis. Cybernetics and systems 29(7), 661–688 (1998)
Walczak, B., Massart, D.L.: Tutorial - Rough sets theory. Chemometrics and intelligent laboratory systems 47, 1–16 (1999)
Soetanto, D.P., Van Geenhuizen, M.: Technology incubators and knowledge networks: a rough set approach in comparative project analysis. Environment and Planning B: Planning and Design 34, 1011–1029 (2007)
Predki, B., Slowinski, R., Stefanowski, J., Susmaga, R., Wilk, S.: ROSE – Software Implementation of the Rough Set Theory. In: Polkowski, L., Skowron, A. (eds.) RSCTC 1998. LNCS (LNAI), vol. 1424, pp. 605–608. Springer, Heidelberg (1998)
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Gizzi, F. et al. (2010). Assessing Macroseismic Data Reliability through Rough Set Theory: The Case of Rapolla (Basilicata, Southern Italy). In: Taniar, D., Gervasi, O., Murgante, B., Pardede, E., Apduhan, B.O. (eds) Computational Science and Its Applications – ICCSA 2010. ICCSA 2010. Lecture Notes in Computer Science, vol 6016. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12156-2_25
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DOI: https://doi.org/10.1007/978-3-642-12156-2_25
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