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Fuzzy hidden Markov model is the efficient way of finding an optimized path among the states where uncertainty exists. Aggregation operators replaced the conventional operators in the fuzzy environment and play a vital role in real-world problems. Here, the aggregation operators namely trapezoidal interval type-2 weighted arithmetic (TpIT2FFWA) and trapezoidal interval type-2 weighted geometric (TpIT2FFWG) operators have been derived and their desired properties also have been proved based on Frank triangular norms. Using the proposed operators and Viterbi algorithm, decision-making process has been analyzed to choose the best medicine company.

Controlling traffic flow on roads is an important traffic management task necessary to ensure a peaceful and safe environment for people. The number of cars on roads at any given time is always unknown. Type-2 fuzzy sets and neutrosophic sets play a vital role in dealing efficiently with such uncertainty. In this paper, a triangular interval type-2 Schweizer and Sklar weighted arithmetic (TIT2SSWA) operator and a triangular interval type-2 Schweizer and Sklar weighted geometric (TIT2SSWG) operator based on Schweizer and Sklar triangular norms have been studied, and the validity of these operators has been checked using a numerical example and extended to an interval neutrosophic environment by proposing interval neutrosophic Schweizer and Sklar weighted arithmetic (INSSWA) and interval neutrosophic Schweizer and Sklar weighted geometric (INSSWG) operators. Furthermore, their properties have been examined; some of the more important properties are examined in detail. Moreover, we proposed an improved score function for interval neutrosophic numbers (INNs) to control traffic flow that has been analyzed by identifying the junction that has more vehicles. This improved score function uses score values of triangular interval type-2 fuzzy numbers (TIT2FNs) and interval neutrosophic numbers.