Spacious complexity reduction of a composite Bayesian decision-making algorithm in an industrial enterprise management information system

I. P. Bolodurina; N. V. Speshilova; V. A. Tripkosh; R. R. Rakhmatullin; E. A. Speshilov

doi:10.1117/12.2669257

5 January 2023 Spacious complexity reduction of a composite Bayesian decision-making algorithm in an industrial enterprise management information system

I. P. Bolodurina, N. V. Speshilova, V. A. Tripkosh, R. R. Rakhmatullin, E. A. Speshilov

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Proceedings Volume 12564, 2nd International Conference on Computer Applications for Management and Sustainable Development of Production and Industry (CMSD-II-2022); 125640Q (2023) https://doi.org/10.1117/12.2669257
Event: Computer Applications for Management and Sustainable Development of Production and Industry (CMSD2022), 2022, Dushanbe, Tajikistan

Abstract

It is advisable to use mathematical modeling of industrial enterprise operating with the help of information technologies when there is a limited number of options, that`s why the problem of acceptable complexity arises while developing decision-making algorithm for computer system recognition in different technical, industrial, economic and management areas. The problem acquires a special importance when the recognition algorithm is based on the compound Bayesian procedures of decision-making which are characterized by a great calculating complexity. The article considers the peculiarities of recognition algorithm operation based on graph-scheme presentation of a priory information to make a decision about the situation class with compound Bayesian procedures. The algorithm complexity is assessed, the approaches to introduce the graph-schemes in the memory of computer systems which reduce the memory requirements are studied. The mathematical methods of graph theory, probability theory, complexity and combinatorial theory are used. The research results in a new method for space complexity reduction of the compound graph-scheme algorithm for situation recognition which enables to provide the efficiency of its calculating complexity. A revised version of the algorithm was suggested. Analytic expressions for calculating parameters of space representation of modified graph-schemes were obtained, their correctness was proved on specific examples.

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I. P. Bolodurina, N. V. Speshilova, V. A. Tripkosh, R. R. Rakhmatullin, and E. A. Speshilov "Spacious complexity reduction of a composite Bayesian decision-making algorithm in an industrial enterprise management information system", Proc. SPIE 12564, 2nd International Conference on Computer Applications for Management and Sustainable Development of Production and Industry (CMSD-II-2022), 125640Q (5 January 2023); https://doi.org/10.1117/12.2669257

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KEYWORDS

Detection and tracking algorithms

Decision making

Algorithm development

Computing systems

Object recognition

Mathematical modeling

Probability theory

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