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Abstract <p>Currently, the use of neural networks allows solving a wide variety of problems: forecasting events, associative information retrieval, product quality control, and many others. In industry, one of the most popular problems to be solved with the help of neural networks is the recognition of visual images. This article discusses the use of neural networks to improve the efficiency and accuracy of manufacturing parts from polymer composite materials (PCMs). An analysis of problems arising at various stages of the technological process of manufacturing parts from PCMs, which can be solved using neural network modeling methods at present, and the prospects for the development of these methods are presented.</p>

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Prospects for the Application of Neural Networks in the Manufacture of Composite Parts

  • 期刊论文

  • 发表日期：

    2025年6月1日

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  • A. A. Baurov

摘要

Abstract

Currently, the use of neural networks allows solving a wide variety of problems: forecasting events, associative information retrieval, product quality control, and many others. In industry, one of the most popular problems to be solved with the help of neural networks is the recognition of visual images. This article discusses the use of neural networks to improve the efficiency and accuracy of manufacturing parts from polymer composite materials (PCMs). An analysis of problems arising at various stages of the technological process of manufacturing parts from PCMs, which can be solved using neural network modeling methods at present, and the prospects for the development of these methods are presented.