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DOI: 10.14489/td.2025.04.pp.062-068 Gushina E. A. Abstract. This paper presents a study of the application of cluster analysis for predicting the properties of polymer composite materials. Clustering methods are considered, which allow efficient grouping of a variety of polymer composites based on specific properties such as mechanical strength, thermal conductivity, electrical conductivity and others. The use of cluster analysis opens up opportunities to reveal hidden patterns and relationships between the components of composites, which in turn helps to optimize their compositions and significantly improve their performance characteristics. The study utilized linear regression method to predict the properties of composite materials based on their composition and process parameters. The results obtained highlight the high efficiency of cluster analysis as an important tool for optimizing the composition of polymer composites and improving their performance characteristics, which may have potential applications in various branches of industry and science. Keywords: cluster algorithms, cluster analysis, database structure, polymer composite materials, prediction of properties, optimization of properties.
E. A. Gushina (Saint Petersburg University of Aerospace Instrumentation, Saint Petersburg, Russia) E-mail: Данный адрес e-mail защищен от спам-ботов, Вам необходимо включить Javascript для его просмотра.
1. Gurenko A. V. (2024). Polymer composite materials in the aerospace industry. Nauchniy aspekt, (6). [in Russian language]
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