The aim of the research is to develop mathematical and program support for detecting abnormal behavior of users. It will be based on analysis of their behavioral biometric characteristics. One of the major problems in UEBA/DSS intelligent systems is obtaining useful information from a large amount of unstructured, inconsistent data. Management decision-making should be based on real data collected from the analysed feature. However, based on the information received, it is rather difficult to make any management decision, as the data are heterogeneous and their volumes are extremely large. Application of machine learning methods in implementation of mobile UEBA/DSS system is proposed. This will make it possible to achieve a data analysis high quality and find complex dependencies in it. A list of the most significant factors submitted to the input of the analysing methods was formed during the research.
This article illustrates the solution of a differential equation describing oscillations of an elastic tensioned guide rail, which consist of string bundle enclosed in an elastic cylindrical shell, while concentrated load, simulated by a material point, moves along it. The oscillatory system is considered in such way that the guide rail supports freely. The existing external and internal forces of resistance to movement of the guide rail are also taken into account. Initial and boundary conditions are zero. In article «A string bend under a moving load», published in the journal «Vestnik BGU. Seriya 1, Fizika. Matematika. Informatika» (2004, No. 1), the deflection of a flexible guide rail under load was obtained by solving an equation with deviating argument. In this article, an algorithm is constructed for finding deflection of an elastic tensioned guide rail in the form of a cubic splines. All the results of calculations are presented in a dimensionless form.
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