Results 241 to 250 of about 154,343 (299)
Some of the next articles are maybe not open access.
Fuzzy Sets and Systems, 1981
Abstract A theory of fuzzy random variables is developed that applies to situations involving both randomness and fuzziness. The use of membership functions that are quasi-concave play an important role in the theory. The expectation of a fuzzy random variable is a fuzzy variable (fuzzy set).
Stein, William E., Talati, Kirit
openaire +2 more sources
Abstract A theory of fuzzy random variables is developed that applies to situations involving both randomness and fuzziness. The use of membership functions that are quasi-concave play an important role in the theory. The expectation of a fuzzy random variable is a fuzzy variable (fuzzy set).
Stein, William E., Talati, Kirit
openaire +2 more sources
Proceedings of 1995 IEEE International Conference on Fuzzy Systems. The International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium, 2002
A strong law of large numbers for non-convex fuzzy random variables is provided, as well as a strong law of large numbers with respect to an extended Hausdorff metric on the set of fuzzy numbers for the class of inverse Lipschitzian fuzzy random variables. >
C. Romer, A. Kandel, M. Friedman
openaire +1 more source
A strong law of large numbers for non-convex fuzzy random variables is provided, as well as a strong law of large numbers with respect to an extended Hausdorff metric on the set of fuzzy numbers for the class of inverse Lipschitzian fuzzy random variables. >
C. Romer, A. Kandel, M. Friedman
openaire +1 more source
Fuzzy Random Variables Revisited
Proceedings of 1995 IEEE International Conference on Fuzzy Systems. The International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium, 1999Reviews the concept of a fuzzy random variable, its expected value, and limit theorems for sequences of fuzzy random variables. The author points out shortcomings in some concepts and results that have been defined in the literature. Finally, the author studies two inequalities involving the expected value of a fuzzy random variable: the Brunn ...
openaire +1 more source
Intuitionistic fuzzy random variables
2011 International Conference on Machine Learning and Cybernetics, 2011Intuitionistic fuzzy set is an extension of traditional fuzzy set, which is considered to be more flexible and applicable than traditional fuzzy set as deal with some uncertain and fuzzy problems. In this paper, some properties of intuitionistic fuzzy set are discussed, intuitionistic fuzzy random variables are first introduced, the expected value of ...
Chao Wang +3 more
openaire +1 more source
Insurance: Mathematics and Economics, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +1 more source
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +1 more source
1988
The definition and properties of the discrete fuzzy random variable are discussed. This extension of a (non-fuzzy) random variable is the appropriate way to model imprecise or fuzzy results of a probabilistic experiment.
William E. Stein, Rami Zwick
openaire +1 more source
The definition and properties of the discrete fuzzy random variable are discussed. This extension of a (non-fuzzy) random variable is the appropriate way to model imprecise or fuzzy results of a probabilistic experiment.
William E. Stein, Rami Zwick
openaire +1 more source
2012
In this chapter, we review some necessary basics of fuzzy random variable, and then lay out the description of the analytical aspects of the fuzzy random variable.
Shuming Wang, Junzo Watada
openaire +1 more source
In this chapter, we review some necessary basics of fuzzy random variable, and then lay out the description of the analytical aspects of the fuzzy random variable.
Shuming Wang, Junzo Watada
openaire +1 more source
Fuzzy Random Variables and Fuzzy Distributions
2021Data sets collected from real experiments are often affected by the randomness, while this information could have an imprecise nature. Therefore, in such random data sets, the probability theory could not always be sufficient for modelling this uncertainty. This latter requires complementary tools.
openaire +1 more source
Gaussian fuzzy random variables
Fuzzy Sets and Systems, 2000\textit{M. L. Puri} and \textit{D. A. Ralescu} [Ann. Probab. 13, 1373-1379 (1985; Zbl 0583.60011)] introduced the concept of Lipschitzian Gaussian fuzzy random variables (f.r.v.) and proved the following representation theorem: Every Gaussian f.r.v. equals the sum of its expectation and a mean zero Gaussian random vector. Using \textit{M.
openaire +2 more sources
Fuzzy random reliability of structures based on fuzzy random variables
Fuzzy Sets and Systems, 1997zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Liu, Yubin, Qiao, Zhong, Wang, Guangyuan
openaire +1 more source