University of Guilan Computational Sciences and Engineering 2783-2503 4 2 2025 08 16 Improved Fuzzy Bayesian Reliability Analysis of Coherent Systems via the‎‎ α‎-Pessimistic Method 283 296 8979 10.22124/cse.2025.31257.1114 EN Mahnaz Mirzayi Department of Statistics, SR.C., Islamic Azad University, Tehran, Iran Reza Zarei Department of Statistics, Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran. Gholamhossein Yari Department of Statistics‎, School of Mathematics‎, ‎Iran University Science and Technology‎, ‎Tehran‎, ‎Iran Mohammad Hassan Behzadi Department of Statistics, SR.C., Islamic Azad University, Tehran, Iran Journal Article 2025 07 23 In real-world reliability analysis, the underlying data and prior knowledge are often imprecise, posing significant challenges to classical probabilistic models. This study presents a novel fuzzy Bayesian approach for analyzing the reliability of coherent systems under imprecise prior information, where system lifetimes follow a Pascal distribution. We construct uncertain Bayes estimators using both squared error and precautionary loss functions by modelling the system reliability as a fuzzy random variable with a prior fuzzy distribution. A key innovation of the proposed approach is the application of the ‎α-pessimistic method, which allows for the estimation process to be carried out without relying on complex non-linear programming, a common limitation in existing literature. Instead, this technique simplifies the computational procedure while enhancing interpretability and analytical tractability. The framework is applied to coherent systems, including parallel, series, and k-out-of-m structures, using Mellin transform techniques to derive the estimators. A numerical example is provided to demonstrate the practical applicability and effectiveness of the proposed method. https://cse.guilan.ac.ir/article_8979_3e06ed9751f8b2ee68101e8e4965782c.pdf