CASPIAN JOURNAL

MANAGEMENT AND HIGH TECHNOLOGIES

Algorithmization of system operation of monitoring and control for solution of identification tasks of damage level of technically complex objects

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Savochkin Alexandr Ye. Algorithmization of system operation of monitoring and control for solution of identification tasks of damage level of technically complex objects // Caspian journal : management and high technologies. — 2014. — №2. — pp. 23-35.

Savochkin Alexandr Ye. - post-graduate student, Penza State Technological University, 1a/11 pr. Baidukova / ul. Gagarina, Penza, 440039, Russian Federation, aebrat@mail.ru

The purpose of this article is to develop algorithm of the solution of identification's tasks of a TCO's status was set, the author considered a system architecture of monitoring and monitoring of technically difficult objects - SMAC TCO - the generalized, single solution of platform level integrating architecture of data, architecture of applications within the hierarchical integrated architecture. During writing of article the upgraded skeleton diagram of SMAC TCO which is turning on the unit of neural network identification was offered. Within the conducted researches the input signal with TCO was processed, selected optimum algorithm of filtering, architecture of multi-layer neural networks were tested, testing and an assessment of accuracy of results of identification was held. After that the optimum architecture of the artificial neural network was selected. By means of simulation of NN TCO (S) damage level for several test signals was revealed and inspections on the accuracy and adequacy are carried out. They testify to high identification abilities of used NN.

Key words: прогнозирование, алгоритм, фильтрация, технически сложные объекты, интеллектуальный анализ данных, нейронная сеть, нейровычисления, идентификация, forecasting, algorithm, filtering, technically difficult objects, data mining, neural network, neuro computi