Пожалуйста, используйте этот идентификатор, чтобы цитировать или ссылаться на этот ресурс: https://dspace.nlu.edu.ua//jspui/handle/123456789/20111
Название: Algorithmization of Intellectual Data Analysis for Measuring the Country’s Innovation Potential
Авторы: Peredrii, O.
Vnukova, N.
Davydenko, D.
Pyvovarov, V.
Hlibko, S.
Opeshko, N.
Ключевые слова: Distribution of input data space
applied intelligent systems
principal component method
innovation potential
Дата публикации: 2024
Издательство: НЮУ ім. Ярослава Мудрого
Библиографическое описание: Peredrii O. Algorithmization of Intellectual Data Analysis for Measuring the Country’s Innovation Potential / O. Peredrii, N. Vnukova, D. Davydenko, V. Pyvovarov, S. Hlibko, N. Opeshko // CEUR Workshop Proceedings : 8th Intern. Conf. on Computational Linguistics and Intelligent Systems, 12–13 April, 2024. – Lviv, 2024. – Vol. 2: Modeling, Optimization, and Controlling in Information and Technology Systems Workshop (MOCITSW-CoLInS 2024). – P. 269–281.
Аннотация: The article examines the key principles of using applied intelligent systems in the economic analysis of Ukraine’s innovation potential, which significantly improves the processes of management algorithm construction and, as a result, creates a favorable environment for innovative development. It presents an algorithm for measuring the country’s innovation potential, which is based on basic methods applied for the analysis, distribution, and classification of input data space. The advantages of applying the principal component method are identified, along with a procedure for using it to determine key indicators for assessing the country’s innovation potential. An approach to determining innovation potential is formed based on intelligent data processing, allowing for the analysis and visualization of large volumes of data, as well as the identification of trends, key factors, and indicators influencing innovation activity in Ukraine. The research also justifies the feasibility and proposes an approach to using modern intelligent systems for continuous monitoring and control of the level of innovation activity, as well as for identifying and forecasting risks and issues, and determining possible ways to address them.
URI (Унифицированный идентификатор ресурса): https://dspace.nlu.edu.ua//jspui/handle/123456789/20111
Располагается в коллекциях:Тези, доповіді кафедри культурології

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