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Position Papers of the 19th Conference on Computer Science and Intelligence Systems

Annals of Computer Science and Information Systems, Volume 40

Applications of new q-rung orthopair fuzzy rough distance measures in pattern recognition and disease diagnosis problems

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DOI: http://dx.doi.org/10.15439/2024F3026

Citation: Position Papers of the 19th Conference on Computer Science and Intelligence Systems, M. Bolanowski, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 40, pages 49–54 ()

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Abstract. As the combined version of rough sets (RSs) and q-rung orthopair fuzzy sets (q-ROFSs), the idea of q-rung orthopair fuzzy rough sets (q-ROFRSs) is more flexible to deal with inaccurate, uncertain and incomplete data. In this manuscript, we propose various q-rung orthopair fuzzy rough distance measures for computing the distance between q-ROFRSs. Some examples are discussed to exemplify the efficacy of developed q-ROFR-distance measures over existing ones. We further demonstrate its utility in pattern recognition and crop disease diagnosis problems. We also establish the superiority of developed distance measures over existing distance measures on q-ROFRSs in view of the structured linguistic variables.

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