Abstract
This paper presents a discussion about two interrelated topics: the definition and use of the probabilistic matrix of system identification in the management and regulation of smart systems, and ways how to refine the models of the functioning of smart systems. The probabilistic identification matrix of the system can be used to study and regulate systems with incomplete statistical data. To solve the second question, the concept of a quasi-fractal algebraic system is introduced, which allows us to look at the problem of forecasting from a different point of view. The concept of an elementary controlled system based on the use of first-order logic methods is also introduced. The level of predictability of the system is established. This paper is of theoretical character. The results obtained in it can be used to regulate learning systems in monitoring the knowledge of students in smart universities and in regulating financial and economic smart systems. In order to achieve these goals, we used the algebraic smart systems’ formalization technique.
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Serdyukova, N., Serdyukov, V., Neustroev, S.: Testing as a feedback in a smart university and as a component of the identification of smart systems. In: Uskov, V., Howlett, R., Jain, L. (eds.) Smart Innovation, Systems and Technologies, SIST, vol. 144, pp. 527–538. Springer (2019)
Serdyukova, N., Serdyukov, V., Slepov, V.: Smart education analytics: quality control of system links. In: Uskov, V., Howlett, R., Jain, L. (eds.) Smart Innovation, Systems and Technologies, SIST, vol. 99, pp. 104–113. Springer (2018)
Mal’tsev, A.: The undecidability of the elementary theory of finite groups. Dokl. Akad. Nauk SSSR 138(4), 771–774 (1961). (in Russian)
Ershov, Yu.: Undecidability of the theories of symmetric and simple finite groups. Dokl. Akad. Nauk SSSR 158(4), 777–779 (1964). (in Russian)
Dubrov, A., Mkhitaryan, V., Troshin, L.: Multivariate Statistical Methods and Fundamentals of Econometrics. Finance and Statistics, Moscow (2002). (in Russian)
Podlazov, A.: Theory of self-organized criticality—the science of complexity. Institute of Applied Mathematics M. V. Keldysh RAS (in Russian)
Danilov, V.: Lectures on Fixed Points. Russian school of Economics, Moscow (2006). (in Russian)
Hutchinson, J.: Fractals and Self-similarity, The Australian National University, Canberra, ACT, 2600, Australia Received March 3, 1980
Serdyukova, N., Serdyukov, V.: Algebraic Identification of Smart Systems. Theory and Practice (in print)
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Serdyukova, N.A., Serdyukov, V.I. (2020). Quasi-fractal Algebraic Systems as Instruments of Knowledge Control. In: Uskov, V., Howlett, R., Jain, L. (eds) Smart Education and e-Learning 2020. Smart Innovation, Systems and Technologies, vol 188. Springer, Singapore. https://doi.org/10.1007/978-981-15-5584-8_37
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DOI: https://doi.org/10.1007/978-981-15-5584-8_37
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