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Open AccessArticle

Integral Seismic Risk Assessment through Fuzzy Models

1
Understanding and Managing Extremes (UME) School, IUSS Pavia, Piazza della Vittoria n.15, 27100 Pavia, Italy
2
Soft Computing Research Group at Intelligent Data Science and Artificial Intelligence Research Center, Universitat Politècnica de Catalunya-BarcelonaTech, Jordi Girona Salgado 1-3, 08034 Barcelona, Spain
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(9), 3017; https://doi.org/10.3390/app10093017
Received: 19 February 2020 / Revised: 19 April 2020 / Accepted: 22 April 2020 / Published: 26 April 2020
The usage of indicators as constituent parts of composite indices is an extended practice in many fields of knowledge. Even if rigorous statistical analyses are implemented, many of the methodologies follow simple arithmetic assumptions to aggregate indicators to build an index. One of the consequences of such assumptions can be the concealment of the influence of some of the composite index’s components. We developed a fuzzy method that aggregates indicators using non-linear methods and, in this paper, compare it to a well-known example in the field of risk assessment, called Moncho’s equation, which combines physical and social components and uses a linear aggregation method to estimate a level of seismic risk. By comparing the spatial pattern of the risk level obtained from these two methodologies, we were able to evaluate to what extent a fuzzy approach allows a more realistic representation of how social vulnerability levels might shape the seismic risk panorama in an urban environment. We found that, in some cases, this approach can lead to risk level values that are up to 80% greater than those obtained using a linear aggregation method for the same areas. View Full-Text
Keywords: composite indices; fuzzy systems; fuzzy models; indicator aggregation; risk assessment; seismic vulnerability; social vulnerability; disaster risk reduction composite indices; fuzzy systems; fuzzy models; indicator aggregation; risk assessment; seismic vulnerability; social vulnerability; disaster risk reduction
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MDPI and ACS Style

G. Cárdenas, J.R.; Nebot, À.; Mugica, F. Integral Seismic Risk Assessment through Fuzzy Models. Appl. Sci. 2020, 10, 3017. https://doi.org/10.3390/app10093017

AMA Style

G. Cárdenas JR, Nebot À, Mugica F. Integral Seismic Risk Assessment through Fuzzy Models. Applied Sciences. 2020; 10(9):3017. https://doi.org/10.3390/app10093017

Chicago/Turabian Style

G. Cárdenas, J. R.; Nebot, Àngela; Mugica, Francisco. 2020. "Integral Seismic Risk Assessment through Fuzzy Models" Appl. Sci. 10, no. 9: 3017. https://doi.org/10.3390/app10093017

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