Abstract
The 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 likely to be affected by an external risk. A meta-multicriteria approach is adopted since the problem itself modulates the multiple criteria method. Firstly, relevant information is grouped into drought sensitivity and adaptive capacity criteria. Ιnstead of the estimation of a unique score for the vulnerability, a classification of the vulnerability to drought into several categories is proposed. Based on the maximum and minimum values of the above criteria initially, four non-ordered categories are established initially to characterize the vulnerability to drought. In order to classify water-scarce countries into the four or more categories the fuzzy pattern recognition is exploited. The proposed approach is applied to estimate drought vulnerability in selected Mediterranean countries. 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 combination of the extreme points.
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Spiliotis, M., Iglesias, A., Garrote, L. (2019). A Meta-multicriteria Approach to Estimate Drought Vulnerability Based on Fuzzy Pattern Recognition. In: Macintyre, J., Iliadis, L., Maglogiannis, I., Jayne, C. (eds) Engineering Applications of Neural Networks. EANN 2019. Communications in Computer and Information Science, vol 1000. Springer, Cham. https://doi.org/10.1007/978-3-030-20257-6_29
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DOI: https://doi.org/10.1007/978-3-030-20257-6_29
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