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Matrix model of data and knowledge presentation to revealing regularities of the fluid flow regime in a pipeline based on hydrodynamics parameters A. E. Yankovskaya, A. Travkov

By: Yankovskaya, Anna EfimovnaContributor(s): Travkov, AMaterial type: ArticleArticleSubject(s): матричная модель | матрица описаний | представление данных и знаний | гидродинамика | режимы течения жидкости | интеллектуальные системыGenre/Form: статьи в журналах Online resources: Click here to access online In: CEUR workshop proceedings Vol. 1903 : DS-ITNT 2017. Data Science. Information Technology and Nanotechnology : proceedings of the International Conference Information Technology and Nanotechnology. Session Data Science, Samara, Russia, 24-27 April, 2017. P. 54-58Abstract: The study offers an original solution to one of the problems of hydrodynamics, namely revealing the regularities in the flow regime of fluid in a pipeline depending on the hydrodynamic parameters. The solution is based on using the intelligent system of the regularities revealing and decision-making. For the first time, a matrix model of data and knowledge representation (MM) is used for these purposes in the form of two matrices: descriptions of the fluid state in the space of characteristic features of hydrodynamics (pressure, velocity, temperature, and others); its rows are associated with various combinations of characteristic features values, and distinguishing of the diagnostic type, whose rows are associated with the corresponding rows of the description matrix, and its columns are associated with the two classifying features. The first classifying features takes four values corresponding to four fluid flow regimes, and the second classifying features takes three values only for the turbulent flow regime value from the first classifying features.
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The study offers an original solution to one of the problems of hydrodynamics, namely revealing the regularities in the flow regime of fluid in a pipeline depending on the hydrodynamic parameters. The solution is based on using the intelligent system of the regularities revealing and decision-making. For the first time, a matrix model of data and knowledge representation (MM) is used for these purposes in the form of two matrices: descriptions of the fluid state in the space of characteristic features of hydrodynamics (pressure, velocity, temperature, and others); its rows are associated with various combinations of characteristic features values, and distinguishing of the diagnostic type, whose rows are associated with the corresponding rows of the description matrix, and its columns are associated with the two classifying features. The first classifying features takes four values corresponding to four fluid flow regimes, and the second classifying features takes three values only for the turbulent flow regime value from the first classifying features.

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