Authors:
Rubén González
1
;
Àngela Nebot
2
;
Francisco Mugica
2
;
Martha-Liliana Carreño
2
and
Alex H. Barbat
2
Affiliations:
1
IUSS, Italy
;
2
Technical University of Catalonia, Spain
Keyword(s):
Fuzzy Sets, Risk Management, Natural Hazards, Vulnerability Index, Social Vulnerability, Seismic Vulnerability, Inference System.
Abstract:
Hazard related Risk is a strange concept since its represents something that has not happened yet, something which is blur and randomness related. Along its estimation, social vulnerability aspects come to arise. Such aspects are even more difficult to define in part because there is still missing a robust way to quantify them and, therefore, to establish a clear analytic framework useful to understand inherent complexities of a human society. In this paper, we build a social aggravation coefficient fuzzy model considering Cardona-Carre˜no aggravation descriptors. By reducing the number of aggravation descriptors and establishing fuzzy logic rules between them, we found similar results in tendency and spatial distribution for seismic resilience and fragility at Barcelona, Spain. We used a classical Mamdani fuzzy approach, supported by well established fuzzy theory, which is characterized by a high expressive power and an intuitive human-like manner. We believe that in this way, a mor
e clear analyses of the resilience and fragility bond can be done exploiting in a more suitable way fuzzy logic capabilities, because the inference process to obtain an aggravation coefficient is based precisely on the establishment of rules (if-then type) directly over the involved variables in social vulnerability formation which allows a smooth application of risk management knowledge, encouraging debate over the used rules, besides the discussion among the employed membership functions.
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