Fuzzy Number

Fuzzy numbers represent imprecise or uncertain numerical values, extending traditional number systems to handle ambiguity inherent in real-world data. Current research focuses on developing robust models and algorithms for handling various types of fuzzy numbers, including Gaussian random fuzzy numbers and shadowed fuzzy numbers, within frameworks like evidential reasoning and multi-criteria decision-making. These advancements improve the accuracy and reliability of predictions and decisions in applications ranging from supplier selection to time-to-event prediction, particularly where uncertainty is significant. The resulting models offer enhanced capabilities for quantifying and managing uncertainty in diverse fields.