Q-rung orthopair normal fuzzy Maclaurin symmetric mean aggregation operators based on Schweizer-Skla operations

In order to be able make a good decision, we need evaluate the uncertainty information of multiple attributes different alternatives that obey normal distribution, and interrelationship among should considered in process evaluating. This paper aims propose new attribute decision-making (MADM) method, which uses aggregation operator distribution comprehensively. We firstly extended Schweizer-Sklar (SS) t-norm (TN) t-conorm (TCN) q-rung orthopair fuzzy number (q-RONFN) defined Schweizer-Skla operational laws set (q-RONFs). Secondly, developed Maclaurin symmetric mean operators based on SS operations considering can reflect input variables. Furthermore, discussed some desirable properties above operators, such as monotonicity, commutativity, idempotency. Lastly, proposed novel MADM method operators. A numerical example enterprise partner selection is given testify effectiveness method. The results analysis indicated our have stronger ability are more general flexible for problems.