Enhanced parameter estimation for Lomax distribution using a contemporary triangular fuzzy ranking method

Abstract

This study presents a novel approach to parameter estimation for the Lomax distribution using a contemporary triangular fuzzy ranking method. The Lomax distribution is critical in reliability analysis and lifetime data modeling but often faces challenges when handling uncertain or imprecise data. Our proposed ranking function for Triangular Fuzzy Numbers (TFNs) enhances the estimation process in fuzzy environments, enabling better interpretation of incomplete datasets. Extensive numerical simulations validate our approach, demonstrating significant improvements over existing methods. • Introduction of a contemporary triangular fuzzy ranking method to improve parameter estimation for the Lomax distribution. • Enhanced processing of incomplete datasets to achieve more reliable estimations in uncertain environments. • Validation through extensive simulations, showcasing the robustness and advantages of the proposed ranking function.

Keywords

• Contemporary triangular fuzzy ranking method