Estimation of the Reliability of the Nitrosophic Transformer Rayleigh Distribution

Abstract

Many of life's problems are full of ambiguity, uncertainty and imprecision, so we need to explain these phenomena. In this research, we present the nitrosophic transformer Rayleigh distribution, which is a generalization of the classical Rayleigh distribution according to the nitrosophic logic. Due to the difficulty of obtaining data in practice, data were obtained in four sizes (25, 50, 100, 150) by generating them from the Rayleigh distribution using the method Simulation, the generated data was converted to nitrosophic using the trigonometric function, and then the data was compensated in the converted Rayleigh distribution to obtain the nitrosophic transformer Rayleigh distribution, and the parameters were estimated and the reliability error of the nitrosophic distribution. Because it contains the least MSE, as for vectors, the non-deterministic vector is the best with respect to the parameter σ and the parameter p. As for the second model, it was found that the sample size of 100 is the best size because it contains the least MSE. As for the vectors, the wrong vector is the best for the parameter σ. As for the parameter p, the real vector He is the best.