An Efficient Neutrosophic Method for Generating Random Variates from Erlang Distribution

Abstract

The simulation process depends on generating a series of random numbers subject to a regular probability distribution in the field [0, 1]. The generation of these numbers is based on the cumulative distribution function of the regular distribution, but we encounter many systems that do not, by nature, follow the regular distribution adopted in the simulation process. Therefore, it is necessary to Convert these random numbers into random variables that follow the probability distribution in which the system to be simulated operates. In classical logic, many techniques can be used in the conversion process, which results in random variables that follow irregular probability distributions. However, the results we obtain are specific results that do not take into account the changes that may occur in the system’s operating environment. To obtain more accurate results, we presented in previous research a study to generate neutrosophic random numbers that follow a regular distribution with no specificity that can be enjoyed by both ends of the field [0, 1]. One or both of them together, and for systems that operate according to probability distributions other than the regular distribution defined in the field [0, 1], we have presented some techniques through which we can obtain neutrosophic random variables based on the neutrosophic random numbers that were generated, in this research and using Previous information: We present a neutrosophic study to generate random variables that follow the Erlang distribution, which is one of the most important and widely used distributions in scientific fields.