Fuzzy Sets and Systems
Single value simulation of fuzzy variables
Fuzzy Sets and Systems
Independence concepts in possibility theory: part I
Fuzzy Sets and Systems
The variance and covariance of fuzzy random variables and their applications
Fuzzy Sets and Systems
On weighted possibilistic mean and variance of fuzzy numbers
Fuzzy Sets and Systems - Theme: Basic concepts
Fuzzy differential equations and the extension principle
Information Sciences: an International Journal
The possibilistic moments of fuzzy numbers and their applications
Journal of Computational and Applied Mathematics
Fuzzy Sets and Systems
Possibilistic mean value and variance of fuzzy numbers: some examples of application
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
A correlation ratio for possibility distributions
IPMU'10 Proceedings of the Computational intelligence for knowledge-based systems design, and 13th international conference on Information processing and management of uncertainty
An improved index of interactivity for fuzzy numbers
Fuzzy Sets and Systems
An improved index of interactivity for fuzzy numbers
Fuzzy Sets and Systems
On possibilistic correlation coefficient and ratio for fuzzy numbers
AIKED'11 Proceedings of the 10th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
On informational coefficient of correlation for possibility distributions
AIKED'12 Proceedings of the 11th WSEAS international conference on Artificial Intelligence, Knowledge Engineering and Data Bases
A generalized 3-component portfolio selection model
AIKED'12 Proceedings of the 11th WSEAS international conference on Artificial Intelligence, Knowledge Engineering and Data Bases
Multidimensional possibilistic risk aversion
Mathematical and Computer Modelling: An International Journal
Computing the Risk Indicators in Fuzzy Systems
Journal of Information Technology Research
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In 2004, Fuller and Majlender introduced the notion of covariance between fuzzy numbers by their joint possibility distribution to measure the degree to which they interact. Based on this approach, in this paper we will present the concept of possibilistic correlation representing an average degree of interaction between marginal distributions of a joint possibility distribution as compared to their respective dispersions. Moreover, we will formulate the classical Cauchy-Schwarz inequality in this possibilistic environment and show that the measure of possibilistic correlation satisfies the same property as its probabilistic counterpart. In particular, applying the idea of transforming level sets of possibility distributions into uniform probability distributions, we will point out a fundamental relationship between our proposed possibilistic approach and the classical probabilistic approach to measuring correlation.