Abstract
Pythagorean fuzzy set (PFS) is a generalization of intuitionistic fuzzy set (IFS), which can express and handle uncertainty in uncertain environment more capable and is widely used in various fields. In the past, several methods of uncertainty measurement of PFSs have been proposed, however, some methods can not provide counterintuitive examples. Therefore, how to measure the uncertainty of PFSs is still an open question. Z-number is a new way to treat uncertainty and reliability of information, Z-number can greatly improve the accuracy and effectiveness of the information fusion process. However, one-dimensional index is not sufficient to express the expert’s assessment. On account of this point, this paper proposes a new uncertainty measurement method between two-dimensional Pythagorean fuzzy sets by using Deng entropy. This method is based on the operation distribution of membership function, non-membership function and hesitation function of two PFSs. Numerical examples show that the proposed method can produce higher identification with more feasible, reasonable and superior result. In addition, by comparing the application of different methods in medical diagnosis, we find that the new algorithm is as effective as other methods. These results prove the practicability of this method in dealing with medical diagnosis problems.
This research is supported by the National Natural Science Foundation of China (No. 62003280), Research Project of Education and Teaching Reform in Southwest University (No. 2019JY053), Fundamental Research Funds for the Central Universities (No. XDJK2019C085) and Chongqing Overseas Scholars Innovation Program (No. cx2018077).
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Fan, Y., Xiao, F. (2020). A Novel Two Dimensional Pythagorean Fuzzy Sets Model with Its Application in Multi-attribute Decision Making. In: Chen, X., Yan, H., Yan, Q., Zhang, X. (eds) Machine Learning for Cyber Security. ML4CS 2020. Lecture Notes in Computer Science(), vol 12488. Springer, Cham. https://doi.org/10.1007/978-3-030-62463-7_39
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