Journal of the Korean Society of Clothing and Textiles (한국의류학회지)

The Korean Society of Clothing and Textiles (한국의류학회)
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Prediction of Fabric Drape Using Artificial Neural Networks

인공신경망을 이용한 드레이프성 예측

  • Lee, Somin (Dept. of Fashion Industry, Ewha Womans University) ;
  • Yu, Dongjoo (Dept. of Fashion Industry, Ewha Womans University) ;
  • Shin, Bona (Dept. of Fashion Industry, Ewha Womans University) ;
  • Youn, Seonyoung (Dept. of Textile Engineering, Chemistry, and Science, North Carolina State University) ;
  • Shim, Myounghee (Korea Textile Trade Association) ;
  • Yun, Changsang (Dept. of Fashion Industry, Ewha Womans University)
  • 이소민 (이화여자대학교 의류산업학과) ;
  • 유동주 (이화여자대학교 의류산업학과) ;
  • 신보나 (이화여자대학교 의류산업학과) ;
  • 윤선영 ;
  • 심명희 (한국섬유수출입협회) ;
  • 윤창상 (이화여자대학교 의류산업학과)
  • Received : 2021.07.16
  • Accepted : 2021.09.06
  • Published : 2021.12.31
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Abstract

This study aims to propose a prediction model for the drape coefficient using artificial neural networks and to analyze the nonlinear relationship between the drape properties and physical properties of fabrics. The study validates the significance of each factor affecting the fabric drape through multiple linear regression analysis with a sample size of 573. The analysis constructs a model with an adjusted R2 of 77.6%. Seven main factors affect the drape coefficient: Grammage, extruded length values for warp and weft (mwarp, mweft), coefficients of quadratic terms in the tensile-force quadratic graph in the warp, weft, and bias directions (cwarp, cweft, cbias), and force required for 1% tension in the warp direction (fwarp). Finally, an artificial neural network was created using seven selected factors. The performance was examined by increasing the number of hidden neurons, and the most suitable number of hidden neurons was found to be 8. The mean squared error was .052, and the correlation coefficient was .863, confirming a satisfactory model. The developed artificial neural network model can be used for engineering and high-quality clothing design. It is expected to provide essential data for clothing appearance, such as the fabric drape.

Keywords

Acknowledgement

본 논문은 2020년도 한국산업기술진흥원 산업기술기반 구축혁신사업의 지원을 받아 수행된 연구임(No. P114000015).

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