Implementation of Statistical Methods to optimize the Processes of Transport Systems

Abstract

Currently, statistical modeling is a very widespread way to simplify the approximation of reality through mathematical descriptions of the systems studied in the form of mathematical models. Model is a very often used simplified abstract tool for predicting the behavior of the modeled systems. When modeling complex transport systems, we encounter phenomena and processes whose input parameters are often random in nature. Their states can be predicted with some probability. In such cases, it is possible to use Monte Carlo methods for statistical prediction of states of continuous random phenomena and subsequent simulation and a sufficient number of generated input parameters of the model to obtain statistical results approaching the state of the modeled system in the real environment. The content of the article is a description of the practical application and use of the Monte Carlo method in statistical modeling in the study and in solving a specific problem in transport systems and optimization of transport processes.