Investigates new convergence methods in fuzzy-valued functions and their implications for approximation.
In this study, we introduce and investigate new forms of convergence, namely, P-statistical relative pointwise, uniform, and P-equi-statistical relative convergence, for sequences of functions whose values lie in the space of fuzzy numbers. These notions, motivated by a synthesis of statistical and relative convergence frameworks, are explored both in terms of their structural characteristics and mutual interrelationships. Furthermore, we examine the behavior of their corresponding r-level sets to provide deeper insight into their convergence dynamics. As a principal application, we apply approximation theorems of Korovkin-type for sequences of functions with fuzzy values under the newly proposed modes of convergence, and we compute the rate of convergence.
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Yıldız et al. (2025) studied this question.
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