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Analysis of medical diagnosis based on fuzzy credibility dombi Bonferroni mean operator

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Abstract

The main aim of this article is to present a novel hybridized idea of fuzzy Credibility Dombi Bonferroni mean aggregation operators to describe the fuzzy Credibility information. Next, we define operational laws of FCNs by using Dombi t-norms and Bonferroni mean operator. By using the proposed operation laws a series of aggregation operators are presented. The TODIM method plays an important rule in decision making problems, especially when the problems of multi criteria group decision making include more computing criteria. So the core of this study is that we have proposed a decision making algorithm based on aggregation information and TODIM method to handle the uncertainty in real life decision making problems under FCNs information. To show the superiority and the applicability of the proposed methods, a numerical case is study of real-life decision making problems in medical diagnosis is considered. Furthermore to indicate the proposed decision making models are much more reliable and efficient to tackle uncertain information based on FCNs information.

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Acknowledgements

This work was supported by the Higher Education Commission (HEC), Pakistan under National Research Program for Universities (NRPU), Project no. 10701/KPK/NRPU/R &D/HEC/2017. Therefore, the authors thankful to NRPU, HEC for financial support.

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Authors and Affiliations

  1. Department of Mathematics, Abdul Wali Khan University Mardan, Mardan, KP, Pakistan

    Muhammad Yahya, Saleem Abdullah & Muhammad Qiyas

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  1. Muhammad Yahya
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  2. Saleem Abdullah
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  3. Muhammad Qiyas
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Correspondence to Muhammad Qiyas.

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Yahya, M., Abdullah, S. & Qiyas, M. Analysis of medical diagnosis based on fuzzy credibility dombi Bonferroni mean operator. J Ambient Intell Human Comput 14, 12709–12724 (2023). https://doi.org/10.1007/s12652-022-04203-2

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