Authors
Zaboev М.
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Degree
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PhD in Economics, Associate Professor, Saint Petersburg State University |
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E-mail
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m.zaboev@spbu.ru |
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Location
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Saint Petersburg |
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Articles
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Evaluation of the prospects Russian universities to be among the first hundred of the world’s leading universities with the use of neural network methods clustering of dataThis article presents the results of research evaluating the positions of the Moscow State University
and the Saint Petersburg State University in the world university rankings by 2020, which is based
on the use of the neural network methods of clustering. The relevance of the chosen research topic
due to implementation of the May 7th, 2012 Presidential Decree N 599 which requires that 5 Russian
universities were join the world’s leading 100 by 2020. The method of clustering based on the selforganizing
Kohonen maps allowed to obtain the following results. The development program of the
SPbSU from the point of view of getting into the top 100 world universities has an insufficient value
of performance indicators and does not include a number of indicators that affect moving up in the
international rankings. The program of the MSU gives some chances to get into the top 100 but it is
necessary to fulfil additional recommendations, developed on the base of clustering model, which
can improve the performance of MSU. In particular MSU recommended to increase indicator Res income
/ Acad staff by 50 thousand USD relative to targets, specified in the development program.
Read more...
Data mining in the management of the Russian higher schoolFor a comprehensive assessment of the management decisions quality, it is necessary to take into account heterogeneous information presented both in numerical form and in natural language expressions. The effective occurs the use of data mining including neural network clustering and fuzzy set theory. The article presents our approach to the use of these methods for evaluating risks and the management decisions quality in Russian higher education on the example of the implementation of the most ambitious Project 5-100 for it. On the example, the expediency of the neural network clustering to assess the possibility of achieving the goals of any such large-scale project has been proved. Clustering the information database used for the analysis, makes it possible to carry out an objective selection of candidate universities-candidates for the right to receive state subsidies, as well as to adjust the composition of the Project participants. Another methods of intellectual analysis – the construction of a complex of fuzzy inference systems, – confirmed the possibility of a quantitative fi evaluating of the project based on the expert verbal estimates of the project. At the same time, the neural network clustering initially illustrated the unattainability of the Project 5-100 goals. The use of a complex of fuzzy inference systems confirmed this statement by the very low quantitative final assessment of the project on the basis of verbal expert opinions. Read more... |
