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This article is cited in 1 scientific paper (total in 1 paper)
Application of decision support methods for the multicriterial selection of multiscale compositions
K. K. Abgaryanab, V. A. Osipovab a Dorodnicyn Computing Center, Federal Research Center “Computer Science and Control” of the Russian
Academy of Sciences, 44/2 Vavilov Str., Moscow, 119333, Russian Federation
b Moscow Aviation Institute (National Research University), 4 Volokolamskoe Shosse, Moscow 125080, Russian Federation
Abstract:
The article discusses the use of decision-making support methods for the task of
selecting multiscale compositions (MC) — computational analogues of multiscale
physical and mathematical models created for analyzing *various heterogeneous
processes associated with the formation of new composite materials with predetermined
properties. When solving specific problems, different multiscale models and their
corresponding MC can be constructed. The question arises of comparing these models
and assessing their “effectiveness” for specific problem. On the stage of predictive
modeling, the authors propose a methodology for comparison of multiscale models
through evaluation and selection of appropriate MC using methods of decision-making
support under multiple criteria. As an illustration of the possibility of choosing the best
alternative in the presence of additional information on evaluation criteria of
MC, a model example associated with the study of electronic and structural
properties of thin films InN (GaN) on silicon substrates is considered.
Keywords:
multiscale modeling, decision theory, quality criteria, alternative, decision support methods, multiple criteria, value function.
Received: 15.11.2018
Citation:
K. K. Abgaryan, V. A. Osipova, “Application of decision support methods for the multicriterial selection of multiscale compositions”, Inform. Primen., 13:2 (2019), 47–53
Linking options:
https://www.mathnet.ru/eng/ia592 https://www.mathnet.ru/eng/ia/v13/i2/p47
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Abstract page: | 201 | Full-text PDF : | 92 | References: | 31 |
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