Saeid Tahmasebi

In dealing with real-world data and models that are consistently and uncertainty, selecting appropriate criteria for measurement and analysis plays a any system. This research examines the importance and efficiency of criteria based on information theory for assessing the degree of uncertainty. The study primarily focuses on generalizations and extended versions of Tsallis exteropy, particulary their application within the framework of Dempster-Shafer evidence theory. In this regard, the theoretical and structural properties of versions of Tsallis exteropy and analyzed and compared and their effectiveness in classification problems is evaluated. The results indicate that the extended criteria based on Tsallis exteropy, especially under conditions of high uncertainty, provide suitable capabilities for assessing ambiguity and improving the decision-making process.