A.V. Skatkov, A.A. Bryukhovetskiy, I.А. Skatkov
Sevastopol State University, RF, Sevastopol, Universitetskaya St., 33
The method of application of spline interpolation in solving the problems of identification of abnormal states (A-events) in information data flows and classification of the specified events in the control of natural and technical objects (NTO) is considered. The approach is based on the representation of the intensity of interface traffic by piecewise linear splines and implemented using a modeling stand. At the first stage, descriptions are generated and formed in the form of linear splines representing the states of controlled objects, one of which is subject to external disturbance. At the second stage, the generated descriptions of splines are used to assess discrepancies between the studied distributions and the influence of a number of factors on the reliability of decisions made using probabilistic modeling methods in the Anylogic environment.
In the process of simulation modeling, it becomes possible to determine and evaluate the totality of the following characteristics: parametrically adjustable threshold values of critical regions; correspondence of the theoretical and empirical distribution of a random variable; areas of reliable recognition of the state of NTO; areas of hypothesis acceptance.
Depending on the purpose of the model, the level of criticality of the objects of control, the expert has the right to set the necessary threshold values of the tuning parameters of the model, for which, on the one hand, high reliability of the controlled values of the characteristics of the objects will be ensured, on the other hand, an acceptable number of errors of the first and second kind is achieved, which means that the risks of making erroneous decisions will be reduced.
The obtained results of the study confirm the stability and sensitivity of the method when choosing threshold values of the intervals that determine the state of NTO.
Keywords: spline interpolation, identification of A-events, probabilistic model, statistical estimates, nonparametric criterion.
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