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Cognitive Prediction Model of University Activity

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Advances in Artificial Systems for Medicine and Education IV (AIMEE 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1315))

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Abstract

The relevance of the problem being solved is due to the need to develop scientifically grounded proposals to achieve the required values of the basic indicators of the university's activity in accordance with the international institutional rating QS to the required values necessary for the university to enter the TOP-500 universities by 2025. To solve this problem, an approach is proposed to the study of weakly structured systems, the class of which includes universities and their activities, based on scenario forecasting methods by building a cognitive model in order to determine the necessary increments of target indicators. The proposed approach makes it possible, under the given constraints, to find the most acceptable scenario for planning the increment of the basic indicators to the target values by identifying the latent factors affecting them and impulse influences (increments) on them, ensuring the guaranteed achievement of the set goal. The results obtained make it possible to subsequently justify the annual costs to ensure an unconditional increase in the values of latent factors with the aim of guaranteed obtaining the required values of the basic indicators by 2025. The novelty of the proposed approach lies in the use of correlations between latent factors, identified on the basis of factor analysis methods, with basic indicators in the construction of a cognitive model, as well as the application of an iterative approach to solving the problem, which makes it possible to update the set of initial data, as well as train the developed cognitive model taking into account the results of identifying latent factors and correcting their correlations. The results obtained make it possible to form the most preferable scenario plan for the necessary stepwise increase in the values of the basic indicators in the interval 2020–2025 subject to resource constraints.

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Acknowledgments

The article was prepared with the support of the Russian Foundation for Basic Research, grants No. 18-07-00918, 19-07-01137 and 20-07-00926.

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Authors and Affiliations

  1. Plekhanov Russian University of Economics, Moscow, Russia

    A. Mikryukov & M. Mazurov

Authors
  1. A. Mikryukov
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  2. M. Mazurov
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Correspondence to A. Mikryukov .

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Editors and Affiliations

  1. International Center of Informatics and Computer Science, Faculty of Applied Mathematics, National Technical University of Ukraine “Kyiv Polytechnic Institute”, Kyiv, Ukraine

    Zhengbing Hu

  2. Laboratory of Biomechanical Systems, Mechanical Engineering Research Institute of the Russian Academy of Sciences, Moscow, Russia

    Sergey Petoukhov

  3. Halmos College of Arts and Sciences, Nova Southeastern University, Ft. Lauderdale, FL, USA

    Matthew He

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Mikryukov, A., Mazurov, M. (2021). Cognitive Prediction Model of University Activity. In: Hu, Z., Petoukhov, S., He, M. (eds) Advances in Artificial Systems for Medicine and Education IV. AIMEE 2020. Advances in Intelligent Systems and Computing, vol 1315. Springer, Cham. https://doi.org/10.1007/978-3-030-67133-4_13

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