Some Results on Convergence in Distribution for Fuzzy Random Sets
نویسندگان
چکیده
In this paper, we first establish some characterization of tightness for a sequence of random elements taking values in the space of normal and uppersemicontinuous fuzzy sets with compact support in Rp. As a result, we give some sufficient conditions for a sequence of fuzzy random sets to converge in distribution.
منابع مشابه
FURTHER RESULTS OF CONVERGENCE OF UNCERTAIN RANDOM SEQUENCES
Convergence is an issue being widely concerned about. Thus, in this paper, we mainly put forward two types of concepts of convergence in mean and convergence in distribution for the sequence of uncertain random variables. Then some of theorems are proved to show the relations among the three convergence concepts that are convergence in mean, convergence in measure and convergence in distributio...
متن کاملRandom intervals as a model for imprecise information
Random intervals constitute one of the classes of random sets with a greater number of applications. In this paper, we regard them as the imprecise observation of a random variable, and study how to model the information about the probability distribution of this random variable. Two possible models are the probability distributions of the measurable selections and those bounded by the upper pr...
متن کاملStrong Convergence for Weighted Sums of Fuzzy Random Variables
In this paper, we establish some results on strong convergence for weighted sums of uniformly integrable fuzzy random variables taking values in the space of upper-semicontinuous fuzzy sets in Rp.
متن کاملConditions of Convergence in Distribution for Random Fuzzy Variables
Fuzziness plays an essential role in the real world. Fuzzy set theory has been developed very fast since it was introduced by Zadeh (1965) [1]. A fuzzy set was characterized with its membership function by Zadeh. The term fuzzy variable was fist introduced by Kaufmann (1975) [2], and then appeared in Zadeh (1978) [3] and Nahmias (1978) [4] as a fuzzy set of real numbers. In order to establish t...
متن کاملA Differential Evolution and Spatial Distribution based Local Search for Training Fuzzy Wavelet Neural Network
Abstract Many parameter-tuning algorithms have been proposed for training Fuzzy Wavelet Neural Networks (FWNNs). Absence of appropriate structure, convergence to local optima and low speed in learning algorithms are deficiencies of FWNNs in previous studies. In this paper, a Memetic Algorithm (MA) is introduced to train FWNN for addressing aforementioned learning lacks. Differential Evolution...
متن کامل