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

Khalilpoor, Parisa; Parchami, Abbas; Pourmousa, Reza

doi:10.22111/ijfs.2026.51406.9082

Document Type : Research Paper

Authors

¹ Department of Statistics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran

² عضو هییت علمی

³ Department of Statistics, Faculty of Mathematics ~and Computer Shahid Bahonar University of Kerman Kerman, Iran

https://doi.org/10.22111/ijfs.2026.51406.9082

Abstract

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 effectively
managed the computational complexity associated with the analysis of fuzzy data. The proposed approach has been applied to model groundwater aquifers distribution.

Keywords

Main Subjects

Decision Making

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Iranian Journal of Fuzzy Systems

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

References

References

Volume 23, Issue 3
May and June 2026
Pages 1-13

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

References

References

Volume 23, Issue 3May and June 2026Pages 1-13

Volume 23, Issue 3
May and June 2026
Pages 1-13