Forecasting University Performance Based On a Cognitive Model
Institute of Digital Economy and Information Technologies Plekhanov Russian University of Economics, Russia, 117997, Moscow, Stremyanny per., 36
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 to the study of weakly structured systems is proposed, based on scenario forecasting methods by building a cognitive model to determine the necessary increments of target values. The proposed approach allows, under the given constraints, to find the most acceptable scenario for planning the increment of basic indicators to target values by identifying the latent factors influencing them and impulse influences (increments) on them, ensuring guaranteed achievement of the set goal. The results obtained made it possible to substantiate the annual costs to ensure an unconditional increase in the values of latent factors (indicators) to guarantee the required values of the basic indicators by 2025.
The novelty of the proposed approach lies in the use, when constructing a cognitive model, of the correlations of latent factors identified on the basis of factor analysis methods with basic indicators, as well as the application of an iterative approach to the solution of the posed problem, which makes it possible to train the developed cognitive model taking into account the results of identification of latent factors and their correction. correlation relationships.
This work was supported by the Russian Foundation for Basic Research within the framework of research projects No. 18-07-00918, 19-07-01137, 20-07-00926.
1. Kuznetsov OP Cognitive modeling of semi-structured situations // [Electronic resource] URL: http://posp.raai.org/data/posp2005/Kuznetsov/kuznetsov.html (Date of access: 14.10.2020).
2. Roberts FS Discrete mathematical models with applications to social, biological and environmental problems. - M .: Nauka, 1986. - 184 p. 13. Kosko B., Fuzzy Cognitive Maps. // International Journal of Man-Machine Studies, (1986) 24, 65-75.