Construction of an Improved Intuitionistic Fuzzy Cloud Theory Performance Evaluation Model
Caichuan Wang, Jiajun Li, Yun He · 2023
Traditional performance evaluation models are difficult to effectively handle a large amount of fuzzy and uncertain information, while intuitionistic fuzzy cloud theory has the advantage of being suitable for solving uncertainty and fuzziness problems. This article analyzed the construction of an improved intuitionistic fuzzy cloud theory performance evaluation model. Based on the principles of intuitionistic fuzzy analytic hierarchy process, indicator weights were constructed, and fuzzy logic and cloud modeling were combined to construct an intuitionistic fuzzy cloud theory performance evaluation model. It was found that the prediction accuracy, accuracy of determining evaluation factor weights, accuracy of overall performance evaluation, and accuracy of decision-making assistance of the improved model were higher than traditional model. The improved intuitionistic fuzzy cloud theory performance evaluation model was more satisfactory to users, with an increase of approximately 12.6% in user satisfaction. This article provided a new perspective for the field of performance evaluation, and was expected to provide new methods.