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MODELING COMPLEX MULTIFACTOR NONLINEAR CONTROL OBJECTS BASED ON A FRAGMENTED NOISY EMPIRICAL HIGH-DIMENSIONAL DATA IN A SYSTEM COGNITIVE ANALYSIS AND IN THE INTELLECTUAL EIDOS-X++ SYSTEM Моделирование сложных многофакторных нелинейных объектов управления на основе фрагментированных зашумленных эмпирических данных большой размерности в системно-когнитивном анализе и интеллектуальной системе «Эйдос-Х++»

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Author(s): Lutsenko Y. V. | Korzhakov V. Y.

Journal: Polythematic Online Scientific Journal of Kuban State Agrarian University
ISSN 1990-4665

Issue: 91;
Start page: 167;
Date: 2013;
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Keywords: COMPUTERIZED SYSTEM-COGNITIVE ANALYSIS | EIDOS INTELLECTUAL SYSTEM | MULTIFACTOR NONLINEAR OBJECTS OF CONTROL | SIMULATION | FORECASTING | DECISION-MAKING

ABSTRACT
In the article, we have considered the application of a system-cognitive analysis and the Eidos-X++ intellec-tual system to create complex multifactor models of nonlinear control objects on the basis of noisy frag-mented empirical data of large dimension and for the use of these models to solve problems of forecasting, executive decision making and research of the model objects. We have formulated the systematic generalization of the principle of Ashby (for nonlinear systems). The numerical example of a study of an abstract nonlinear system (Lissajous figures), in which the combined effect of multiple factors is the sum of the influences of each of these factors separately, that says about non-compliance of these factors, the principle of superposition and nonlinear effects in the system under consideration. It is shown, that the proposed device and software tools allow us to model such systems. We note, that the proposed device and instrumentation allow to interpret some classification scale, as projected geographical coordinates of the event, and others, like the foreseeable events and their severity, which allows you to get cartographic visualization of recognition of the place and time of events
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