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Title: Calculation Methods of the Prognostication of the Computer Systems State under Different Level of Information Uncertainty
Other Titles: Методи розрахунку прогнозування стану комп'ютерних систем при різному ступені невизначеності інформації
Методы расчета прогнозирования состояния компьютерных систем при различной степени неопределенности информации
Authors: Атаманюк, Ігор Петрович
Атаманюк, Игорь Петрович
Atamanyuk, Igor
Кондратенко, Юрій Пантелійович
Кондратенко, Юрий Пантелеевич
Kondratenko, Yuriу
Шебанін, В’ячеслав Сергійович
Шебанин, Вячеслав Сергеевич
Shebanin, Vyacheslav
Keywords: calculation method
random sequence
canonical decomposition
prognostication of the state
mathematical model
метод расчета
случайная последовательность
каноническое разложение
прогнозирование состояния
математическая модель
метод розрахунку
випадкова послідовність
канонічне розкладання
прогнозування стану
математична модель
Issue Date: 2016
Citation: Atamanyuk I. Calculation Methods of the Prognostication of the Computer Systems State under Different Level of Information Uncertainty / I. Atamanyuk, V. Shebanin, Yu. Kondratenko // Proceedings volume of 2nd International Workshop on Theory of Reliability and Markov Modeling for Information Technologies (TheRMIT) in ICTERI 2016, Kyiv on the 21st-24-th of June. – Kyiv, 2016. – pp. 292-307.
Abstract: Calculation methods of the prognostication of the computer systems state under different volume of a priori information and accuracy of the meas-urement of controlled parameters (under absence and presence of measurement errors) are obtained in the work. Canonical expansions of random sequences of the indices characterizing the state of the investigated systems considered as ba-sic features of the methods. Synthesized methods do not impose any significant limitations on the qualities of the sequence of the change of the forecast pa-rameters (linearity, stationarity, Markov behavior, monotoneness, etc.) and al-low to take into account the stochastic peculiarities of the process of function-ing of the investigated objects as much as possible. Expressions of the determi-nation of a mean-square extrapolation error are obtained for solving the prog-nostication problems specifically concerning the state of computer systems un-der different level of information uncertainty.
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