Abstract
The first objective of this paper is to explore a new integrated approach to estimate drought vulnerability taking into account the characteristics of a system that make it prone to be affected by an external hazard. The second objective is to investigate the link between fuzzy pattern recognition and distance based multi-criteria categorization oriented to the assessment of the vulnerability to drought. Firstly, relevant information is grouped into drought sensitivity and adaptive capacity criteria. Instead of the estimation of a unique score for the vulnerability, we propose a classification of the vulnerability to drought into several, in general, non ordered categories. Initially, only the ideal and the anti-ideal points are considered. The link with the multicriteria technique for order preference by similarity to ideal solution (TOPSIS) is investigated. Next, many non-ordered categories are considered which are modulated from all the combinations of the extreme points. Finally, the original fuzzy pattern recognition is considered where the centres are not selected a priori but based on the sample itself. A choice that strengthens the meta-multicriteria character of the proposed approaches is that the categories are not ordered, but they are modulated from all the combinations of the extreme points.
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Spiliotis, M., Iglesias, A. & Garrote, L. A multicriteria fuzzy pattern recognition approach for assessing the vulnerability to drought: Mediterranean region. Evolving Systems 12, 109–122 (2021). https://doi.org/10.1007/s12530-020-09332-7
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DOI: https://doi.org/10.1007/s12530-020-09332-7