JOURNAL OF TEXTILE RESEARCH ›› 2018, Vol. 39 ›› Issue (07): 116-121.doi: 10.13475/j.fzxb.20170901006

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Generation of intelligent fitting pattern based on BP neural network

  

  • Received:2017-09-04 Revised:2018-03-28 Online:2018-07-15 Published:2018-07-16

Abstract:

In order to quickly obtain a clothing model fitting the customer's body shape, the men's trousers were used as the reference model, and the rules for changing the waist and hip areas were used as research subjects. Gerber CAD was used as a technology development platform. Based on a large quantity of human body data, the original change rules of the templates were optimized and reconstructed.The BP neural network algorithm was used to establish the waist and hip circumference size changes. By kirectly using the matching of data and tata, the parametric design of men's waistband, abdomen and hip modification rules was realized. In other words, in a given amount of waist and hip circumference, a corresponding change rule can be acquired. By calling the chaneg rule a sample coming in line with the size will the size will be automatically achived, initially realizing one person and one board. The clothing fitting is improved and the dependence on modelers is reduced.

Key words: clothing model, BP neural network, intelligent plate, male tailored trousers, customization

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