Modeling bivariate distributions with triangular fuzzy data and its application in hydrological studies: A copula-based approach

Fuzzy data analysis presents significant computational challenges due to its inherent ambiguity and uncertainty. Traditional statistical methods do not have the capability to effectively capture and model the uncertainty in fuzzy observations. A novel approach is proposed in this paper to model unknown bivariate densities using fuzzy observations and incorporating the dependency between variables. By employing this copula-based approach, we have effectivelymanaged the computational complexity associated with the analysis of fuzzy data. The proposed approach has been applied to model groundwater aquifers distribution.

کلیدواژه ها:

bivariate density estimation ، fuzzy-valued data ، FGM copula ، AMH copula ، Gaussian copula