This paper introduces the generalized fuzzy contraction in k-fuzzy metric spaces, a novel extension of the classical Meir-Keeler contraction principle. The main discovery is that several fixed point theorems, previously limited to classical or fuzzy metric spaces, remain valid under more general k-fuzzy conditions. This breakthrough broadens the applicability of fixed point theory to systems with multi-parameter uncertainty and non-uniform convergence, thereby offering a new mathematical tool for analyzing complex real-world problems in control theory, optimization, and data science.
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