A meta-multicriteria approach to estimate drought vulnerability based on fuzzy pattern recognition

4Citations
Citations of this article
2Readers
Mendeley users who have this article in their library.
Get full text

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.

Cite

CITATION STYLE

APA

Spiliotis, M., Iglesias, A., & Garrote, L. (2019). A meta-multicriteria approach to estimate drought vulnerability based on fuzzy pattern recognition. In Communications in Computer and Information Science (Vol. 1000, pp. 349–360). Springer Verlag. https://doi.org/10.1007/978-3-030-20257-6_29

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free