Abstract
A method for generating adaptive decision support systems is examined in this paper. Models, algorithms, and programming technology making possible the use of knowledge of distributed experts for system adaptation to environmental variation that increases its life-cycle and the efficiency of decision-making processes are presented. The multicomponent adaptive model of a subject domain for the problem on decision-making and algorithms of structure and information adaptation of the model are given. The open architecture of the adaptive decision support system in federation form is also presented. The architecture is developed according to the concept of distributed simulation standard High Level Architecture and it secures component compatibility, interaction possibility, and reuse.
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Karkanitsa A.V. was born in 1974, and educated at the Yanka Kupala State University of Grodno. She is the senior teacher of Faculty of Mathematics & Computer Sciences, Yanka Kupala State University of Grodno. Her fields of scientific interests include artificial intelligence, pattern recognition, and systems for supporting decision making. She is the author of 29 scientific publications.
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Karkanitsa, A.V. Models, Algorithms, and Architecture for Generating Adaptive Decision Support Systems. Pattern Recognit. Image Anal. 30, 174–183 (2020). https://doi.org/10.1134/S1054661820020066
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DOI: https://doi.org/10.1134/S1054661820020066