Using Data Mining Techniques for the Management of Seismic Vulnerability


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Natural hazards, and especially earthquakes, are often recurring phenomena. Therefore, there is a permanent need for solutions to reduce earthquake losses by developing technologies, procedures, knowledge, and tools for seismic design and rehabilitation of buildings and infrastructure. A key point to an effective decision making process that aims at mitigating their effects is building a model of the underlying facts. A Geographical Information System (GIS) is a framework able to assemble, keep, process and display specific information, identified by geographical location, which can combine layers of information to give the user a better understanding about that location. By using a Geographical Information System containing geospatial data, one can develop useful scenarios to reduce natural disaster risk and vulnerability of structures. In this paper, we describe a way of applying data mining techniques from the artificial intelligence field to earthquake analysis in order to make a better investigation of the available data. These methods are capable of finding “hidden” correlations among different subsets of data, which cannot be revealed by means of simple statistics.



Key Engineering Materials (Volumes 326-328)

Edited by:

Soon-Bok Lee and Yun-Jae Kim




F. Leon et al., "Using Data Mining Techniques for the Management of Seismic Vulnerability", Key Engineering Materials, Vols. 326-328, pp. 501-504, 2006

Online since:

December 2006




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