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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/28098
Title: Software for evaluating the electronic safety system reliability in case of large volume of data about its technical conditions availability
Authors: Dzik, S. S.
Tsyrelchuk, N. I.
Borovikov, S. M.
Tsyrelchuk, I. N.
Dzik, S. К.
Zhidiliaeva, N. I.
Дик, С. С.
Цырельчук, Н. И.
Боровиков, С. М.
Цырельчук, И. Н.
Дик, С. К.
Жидиляева, Н. И.
Keywords: материалы конференций
software
evaluating the electronic safety system
technical conditions availability
Issue Date: 2017
Publisher: БГУИР
Citation: Software for evaluating the electronic safety system reliability in case of large volume of data about its technical conditions availability / S. S. Dzik and others // BIG DATA and Advanced Analytics: collection of materials of the third international scientific and practical conference, Minsk, May 3–4 2017 / editorial board : М. Batura [etc.]. – Minsk : BSUIR, 2017. – С. 139 - 143.
Abstract: Evaluation of the design reliability of a complex electronic system causes many difficulties. This is a consequence of an excessive number of possible technical states of the system. In a number of cases, the number of these states and the data volumes for their description is so large that they fall under the notion of Big data. As the result, the usual methods of processing such volumes of data are not possible. As a way out of the situation, we propose to use the simplification of analysis which is based on the decomposition of the system. We have developed software for applying the decomposition method to assess the reliability of electronic security systems. It allows you to build a protected object (the building plan with its premises) in an interactive mode with the help of a computer, place the components of an electronic security system in the premises, allocate subsystems and per- form their analysis in terms of the reliability and protection of the premises.
URI: https://libeldoc.bsuir.by/handle/123456789/28098
Appears in Collections:BIG DATA and Advanced Analytics. Использование BIG DATA для оптимизации бизнеса и информационных технологий (2017)

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