Application of BP Neural Networks in Garment Pattern Design System.

Comput Intell Neurosci

College of Fine Arts and Design, Hebei Institute of Communications, Shijiazhuang 050000, China.

Published: May 2022

AI Article Synopsis

  • The apparel market is facing increased competition due to globalization and advancements in information technology, making it essential for China's garment industry to adopt informatization to stay competitive internationally.
  • Mass customization of garments is becoming a key trend, as consumers seek personalized options in style, fabric, and fit, which traditional hand-made methods cannot efficiently fulfill due to the diverse body types in China.
  • This study introduces an intelligent garment paper sample design system powered by BP neural networks, aiming to enhance design efficiency and quality by reducing reliance on operator skills through self-learning and adaptive capabilities.

Article Abstract

With the intensification of global market competition and the continuous development of the information technology, competition in the apparel market has become increasingly fierce. The key to whether China's garment industry can maintain its advantage in the international market competition in the future lies in whether it can promote and realize the informatization of the garment industry or not. After all, under the context of increasingly developed information technologies and growing competition in the garment market, mass customization of garments has become a future trend in the garment industry. As custom-made clothing is more in line with consumers' individual needs in terms of style, fabric, and size, the focus of development for clothing companies is increasingly on the grasp of the fit of clothing. However, with China's large population and the wide variety of body types, traditional hand-made garments are time-consuming and cannot meet the differentiated needs of consumers in the modern market. The design of garment samples is an important part of the industrial production of garments and is highly dependent on the skills and experience of the operators. In other words, the level of technical expertise can determine the quality and shape of a garment product to a certain extent. As a result, in order to further improve the efficiency and quality of garment sample design and to reduce the dependence on operator skills and experience, this study proposes an intelligent garment paper sample design system based on BP neural networks. The system mainly utilizes the self-learning, self-organizing, and adaptive as well as nonlinear mapping functions of artificial neural networks to design clothing samples autonomously, thus improving the design efficiency. In the era of rapid development of information technology and artificial intelligence technology, the development of intelligent garment pattern design systems with independent intellectual property rights is of great significance in promoting the prosperity of the garment industry.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9113887PMC
http://dx.doi.org/10.1155/2022/8766137DOI Listing

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