Title :
Study on prediction model for seamless underwear fitness in comfortable apparel pressure
Author :
Jin, Zi-min ; Yan, Yu-xiu ; Yu, Shi-jia ; Tao, Jian-wei
Author_Institution :
Key Lab. of Adv. Textile Mater. & Manuf. Technol., Zhejiang Sci-Tech Univ., Hangzhou, China
Abstract :
Focus on the selects 4 pieces of women seamless underwear with the character of the same style, yarn and weaving mode and different size, this paper, through the young woman trying on the samples, measures the pressure of each part´s test pints and gives the subjective assessment of comfort to the parts. With the method of fuzzy math to preprocess test datum, regression analysis is used to process the fitness and pressure values of seamless underwear´s 6 parts to get the prediction regression models. By applying the statistic methods of parameter interval estimation to obtain the pressure comfort ranges of body parts, seamless underwear´s fitness is foresaw whether is reasonable by combing prediction regression models and pressure comfort ranges, which provides basis of related specifications for seamless garment enterprises.
Keywords :
clothing; fuzzy set theory; regression analysis; apparel comfortable pressure; fuzzy math method; prediction regression models; regression analysis; seamless garment enterprises; seamless underwear fitness; women seamless underwear; Clothing; Parameter estimation; Predictive models; Pressure measurement; Regression analysis; Size measurement; Statistics; Testing; Weaving; Yarn; Fitness; Prediction model; Pressure comfort; Seamless underwear; Women´s upper body;
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
DOI :
10.1109/ICMLC.2009.5212446