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This article is cited in 6 scientific papers (total in 6 papers)
Support for solving diagnostic type problems
M. I. Zabezhailoa, A. A. Grushob, N. A. Grushob, E. E. Timoninab a A. A. Dorodnicyn Computing Center, Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 40 Vavilov Str., Moscow 119333, Russian Federation
b Institute of Informatics Problems, Federal Research Center "Computer Sciences and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow
119133, Russian Federation
Abstract:
Some significant features of mathematical methods of data analysis and decision support in diagnostic-type problems are discussed. The most significant characteristic features are considered allowing to distinguish the tasks of the discussed type into a special class. This class requires the simultaneous development of solutions to a number of interrelated problems which, without taking into account such relationships, are practically useless. Using the experience with diagnostic-type tasks, recommendations are made on the areas of development of effective approaches and methods of data mining for solving such applications.
Keywords:
artificial intelligence, intelligent data analysis, mathematical methods, diagnostics.
Received: 09.02.2021
Citation:
M. I. Zabezhailo, A. A. Grusho, N. A. Grusho, E. E. Timonina, “Support for solving diagnostic type problems”, Sistemy i Sredstva Inform., 31:1 (2021), 69–81
Linking options:
https://www.mathnet.ru/eng/ssi750 https://www.mathnet.ru/eng/ssi/v31/i1/p69
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