Abstract

Machine learning is a major trend in today's world. Machine learning algorithms are used in almost every area of human life. One of these areas is the creation of new composite materials. Composite materials are used everywhere, from dental prosthetics to aircraft construction. Composite materials allow you to endow familiar things with new properties. For example, lightening the mass of unmanned aerial vehicles. Another example is the creation of such materials that are able to have increased strength to create new wear-resistant road surfaces. Combining such two areas of research as machine learning and composite materials will allow the creation of new materials with unique properties. Machine learning algorithms allow you to find dependencies that a person could not find before due to the fact that the amount of information being processed is huge. This study is aimed at developing algorithms for predicting the strength failure of composite materials using machine learning methods.

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