A strong law of large numbers for fuzzy random sets

1991 ◽  
Vol 41 (3) ◽  
pp. 285-291 ◽  
Author(s):  
Hiroshi Inoue
2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
R. Ghasemi ◽  
A. Nezakati ◽  
M. R. Rabiei

The main purpose of this paper is to consider the strong law of large numbers for random sets in fuzzy metric space. Since many years ago, limited theorems have been expressed and proved for fuzzy random variables, but despite the uncertainty in fuzzy discussions, the nonfuzzy metric space has been used. Given that the fuzzy random variable is defined on the basis of random sets, in this paper, we generalize the strong law of large numbers for random sets in the fuzzy metric space. The embedded theorem for compact convex sets in the fuzzy normed space is the most important tool to prove this generalization. Also, as a result and by application, we use the strong law of large numbers for random sets in the fuzzy metric space for the bootstrap mean.


Author(s):  
Li Guan ◽  
Jinping Zhang ◽  
Jieming Zhou

This work proposes the concept of uncorrelation for fuzzy random variables, which is weaker than independence. For the sequence of uncorrelated fuzzy variables, weak and strong law of large numbers are studied under the uniform Hausdorff metric d H ∞ . The results generalize the law of large numbers for independent fuzzy random variables.


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