Внедрение и адаптация методов математического моделирования нелинейных процессов на примере эксплуатации транспортных средств и специальной техники

Abstract

The modern mathematical modeling methods provides a comprehensive toolkit for handling a most of data, on another hand more complicated tasks requires logic with higher computational complexity, which means a considerable influence at a Big Data handling. The most suitable method selection is a search of a compromise solution with the necessary accuracy and admissible computational complexity. Moreover, methods are to be adapted to the certain solution aimed at providing the greatest match of the modeling results to process class. This article discusses the selecting and adaptation of mathematical modeling methods to vehicles and heavy equipment MRO costs, which are a result of two different processes: regular maintenance and accidental repair that may be delayed due to the situation reasons. The work done not only allows to make a longterm (thirty years) forecast using accumulated during a short time (three years) statistics, but also provides a toolkit to handle a wide range of data including non-linear and stochastic processes.