Data mining-based optimal assignment of apparel size for mass customization

Data mining-based optimal assignment of apparel size for mass customization

In this study, we have explored and discussed the data mining-based solutions to apparel size assignment using approach principle, K-means clustering, and support vector machine, respectively. A case of mass customization for men's pants in China with 200 adult males were employed to validate a...

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Autores principales: Zhujun Wang, Cheng Chi, Mengyun Zhang, Xianyi Zeng, Pascal Bruniaux, Jianping Wang, Yingmei Xing
Formato: article
Lenguaje:EN
Publicado: TU Dresden; Faculty of Mechanical Science and Engineering;Chair of Development and Assembly of Textile Products 2020
Materias:
garment size
mass customization
data mining
clustering algorithm
k-means clustering
support vector machine
Textile bleaching, dyeing, printing, etc.
TP890-933
Engineering machinery, tools, and implements
TA213-215
Acceso en línea:https://doaj.org/article/553eb18e256d4e0696ac959fae0bbbcb
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