Innovative art selection through neutrosophic hesitant fuzzy partitioned Maclaurin symmetric mean aggregation operator

The neutrosophic hesitant fuzzy set is the union of the neutrosophic set and hesitant fuzzy set in which each element has membership, neutrality, and non-membership arrays which verifies infrequency in labeling uncertainty in daily usage. We proposed two novel operators in this analysis that demonstrate evolution, one is the neutrosophic hesitant fuzzy partitioned Maclaurin symmetric mean (NHFPMSM) and the other is the neutrosophic hesitant fuzzy weighted partitioned Maclaurin symmetric mean (NHFWPMSM). These novels aim to draw inspiration from the partitioned Maclaurin symmetric mean concept. The diverse properties and special cases of these operators are demonstrated in this article. We introduce a novel multiple-criteria decision-making method based on the NHFWPMSM operator for choosing the most appropriate substitute from a set of choices ideally. We highlight an organized technique using our approach for selecting the most unique and the best piece of art that focuses on a better composition with appealing colors for innovative art patterns. Moreover, this article shows expert frequency and productiveness through comprehensive contrasting studies and that is how our progressive access excels in existing strategies.