Generating Neutrosophic Random Variables Based Gamma Distribution

Abstract

In practical life, we encounter many systems that cannot be studied directly, either due to their high cost or because some of these systems cannot be studied directly. Therefore, we resort to the simulation method, which depends on applying the study to systems similar to real ones and then projecting these results if they are suitable for the real system. The simulation process requires a good understanding of probability distributions and the methods used to transform random numbers that follow a regular distribution in the field [0,1] into random variables that follow them, so that we can achieve the greatest possible benefit from the simulation process and obtain more accurate and appropriate results for all conditions that arise. In previous research, we presented a neutrosophical vision of the process of generating random numbers that follow a regular distribution in the field [0, 1] and some techniques used to generate random variables, such as the inverse transformation technique that was used to generate random variables that follow a uniform distribution in the domain [a, b] and the exponential distribution, the rejection and acceptance technique, which was used to generate random variables that follow the beta distribution, and the mixed technique, which was used to generate random variables that follow the Poisson distribution. In this research, we present a neutrosophic study to generate neutrosophic random variables that follow the gamma distribution, a distribution that is frequently used in engineering applications.