Dugina Tat'yana Olegovna, Postgraduate student, Penza State University (40 Krasnaya street, Penza, Russia), firstname.lastname@example.org
Background. Data, obtained bench tests of propulsion systems, should be processed correctly by decision-making support systems. From the point of view of a developer of such systems there are some implementation issues, associated with searching of highly effective methods for data representation. There is a problem of
representation of complex multidimensional data. The aim of this work is to create a certain model, which can represent a set of simple and multidimensional data using three-dimensional graphics’ resources.
Materials and methods. The author used methods of image theory, artificial intelligence in image recognition, automated synthesis of graphic images and human perception basics. The achieved results are based on the works by such authors as P. Kolers, U. Grenander, G. Breslav and other.
Results. For the first time the author has proposed a tunnel data model which is a kind of graphical data model and it is highly compact and easy-to-see. The proposed model is a generalized graphical pattern, which is sufficient for making a decision by an operator of the decision-making support system. The paper considers a possibility of building a tunnel model for a set of simple and multidimensional data. The procedure of tunnel data normalization is described.
Conclusions. The presented tunnel data model has scientific novelty and practical demand; it demonstrates operational comfort when displaying large amounts of data, which are obtained from bench tests. It allows to reduce the results to generalized tunnels, to arrange the measured parameters inside the calculated ones, and the latter inside the calculated parameters of greater degree of enclosure. The suggested model provides a decision-making person with a convenient method in various time sections and projections.
tunnel model, generalized graphical pattern, graphical data representation, bench tests data, multidimensional dependencies, multidimensional data, tabular data representation, decision-making support system.
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