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Three-Dimensional System-Object Classification for Prediction and Control Support

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Abstract

The disadvantages of modern methods of classifying objects and processes are considered. We propose a method of constructing three-dimensional classifications that allows the elimination of some of these shortcomings, based on the system-object approach, using the ideas of multidimensional classification and natural classification. Three basic system characteristics are used as classification planes: structural (node), functional (function), and substantive (object), which allows for the classification by types of functional request to the system from a higher-order system (supersystem) by types of system formation processes and by the obtained results. Each classification is a tree-type graph with one vertex that is common to all three planes. The formal description of the three-dimensional graph by means of descriptive logic is presented, which not only allows for the phenomena and objects of the subject area to be classified, but also for the cause-and-effect relations existing in this area to be traced. The procedures for the use of three-dimensional system-object classification for forecasting and management support are described. An example of three-dimensional classification for functional diagnostic devices is given.

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This work was supported by ongoing institutional funding. No additional grants to carry out or direct this particular research were obtained.

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Authors and Affiliations

  1. Belgorod State National Research University, Belgorod, Russia

    S. I. Matorin, S. V. Gul & N. V. Shcherbinina

  2. Belgorod University of Cooperation, Economics and Lawn, Belgorod, Russia

    S. I. Matorin

Authors
  1. S. I. Matorin
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  2. S. V. Gul
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  3. N. V. Shcherbinina
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Correspondence to S. I. Matorin, S. V. Gul or N. V. Shcherbinina.

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Translated by V. Terechshenko

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Matorin, S.I., Gul, S.V. & Shcherbinina, N.V. Three-Dimensional System-Object Classification for Prediction and Control Support. Autom. Doc. Math. Linguist. 57, 350–361 (2023). https://doi.org/10.3103/S0005105523060067

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