Abstract
The Tsallis entropy has high performance in handling uncertain information, which is the extension of information entropy. The extropy is a complementary dual of entropy, which is a research hot spot. This paper proposed the Tsallis eXtropy and maximum Tsallis eXtropy, which are the complementary of Tsallis entropy and maximum Tsallis entropy respectively. When the non-extensive parameter is equal to 1, then the Tsallis eXtropy and the maximum Tsallis eXtropy will degenerate into information extropy and maximum information extropy respectively. Some meaningful theorems and proofs of the Tsallis eXtropy and the maximum Tsallis eXtropy has been proposed. Numerical examples have been designed to prove the effectiveness of the proposed models in evaluating uncertainties. Comparison application has been applied to prove the superiority of the proposed models than other models. The experimental results have shown that the proposed models are very high effective in measuring unknown issues.
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