Determination of Deviation Risk of an Event from Mathematical Expectation When Managing Research in Space and Time

Abstract

Abstract The paper analyses various time segments of a random process and shows how the covariance of the values of random functions for different times is displays. It is accepted that any type of management involves the optimal use of factors, avoiding the uncertainties that are inevitable with a statistical approach to the sequencing of scientific research. The model includes the risk minimization of the real process deviation from the anticipated one. The concept of the quasi-ergodic idea of two functions, which characterize this concept with the corresponding form of integrals, is important for a further understanding of the presented theory. Various time segment of a random process are analyzed during the scientific research, and it is shown how the covariance of random functions’ values for times is manifested. The proposed model allows us to expand the boundaries of the automation of the research management process in space and time, taking into account the risk associated with the use of factors of the digital model.