Is it correct to compare the uncertain (fuzzy, neutrosophic etc. ) measure with classical or deterministic measure?. I need efficiency comparison criteria for developed fuzzy estimator for parameter of fuzzy and neutrosophic variable
Yes, it is correct to compare uncertain measures with classical or deterministic measures. In fact, this comparison is important in many real-world applications where uncertainty and vagueness play a significant role.
Uncertain measures, such as fuzzy measures, neutrosophic measures, and probability measures, can be compared to classical or deterministic measures in terms of their ability to model and handle uncertainty and vagueness. For example, probability measures are widely used in classical statistics and decision-making, while fuzzy measures and neutrosophic measures provide more flexible ways of dealing with uncertainty and vagueness.
In general, the choice of measure depends on the specific problem at hand and the type of uncertainty or vagueness involved. For example, probability measures are often preferred for modeling objective and well-defined uncertainty, while fuzzy measures and neutrosophic measures may be more suitable for modeling subjective and ill-defined uncertainty.