Сибирский федеральный университет

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: International Scientific and Practical Conference on New Behaviors of Market Players in the Digital Economy; Inst Sci Commun, ELECTR NETWORK; Inst Sci Commun, ELECTR NETWORK

Год издания: 2022

Идентификатор DOI: 10.1007/978-3-030-93244-2_10

Ключевые слова: development institutions, logistic regression, operations research, scientific expertise, systems analysis

Аннотация: Development institutes act as a major driving factor in the development of innovations. Therefore, they must use effective and progressive methods of work. In this study, we aim to develop a mechanism for compiling the list of projects to be reviewed by the expert council for further financial support. The mechanism is based on the methods of system analysis and operations research. The study was conducted on the example of project applications to the contests of the Krasnoyarsk Regional Science Foundation. We constructed a logistic regression model using a binary linear classifier based on the contest application review. As a result, we determined the lower limit for the inclusion of a project in the short-list. By comparing the resulting project criteria with the actual results of the review, we received a condensed list of projects that eliminates the influence of the human factor on the contest result. This model is universal and can be scaled up to other development institutions if adjusted as necessary. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Журнал: Lecture Notes in Networks and Systems

Выпуск журнала: Vol. 368 LNNS

Номера страниц: 80-87

ISSN журнала: 23673370

Издатель: Springer Science and Business Media Deutschland GmbH

• Panteleeva I.A. (Siberian Federal University, Krasnoyarsk, Russian Federation)
• Parfenteva K.V. (Krasnoyarsk Regional Fund for Support of Scientific and Technical Activities, Krasnoyarsk, Russian Federation)
• Shan’ko Y.V. (Institute of Computational Modelling of SB RAS, Krasnoyarsk, Russian Federation)
• Byvshev V.I. (Siberian Federal University, Krasnoyarsk, Russian Federation)
• Demin V.G. (Siberian Federal University, Krasnoyarsk, Russian Federation)

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