A Matching Degree Management Model of Human Body Shape and Fashion Design Based on Big Data Analysis | Zendy

Yumei Cui | Zendy; Xinqun Feng | Zendy; Xinxin Yang | Zendy

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A Matching Degree Management Model of Human Body Shape and Fashion Design Based on Big Data Analysis

Author(s) -

Yumei Cui,

Xinqun Feng,

Xinxin Yang

Publication year - 2021

Publication title -

scientific programming

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.269

H-Index - 36

eISSN - 1875-919X

pISSN - 1058-9244

DOI - 10.1155/2021/9384404

Subject(s) - matching (statistics) , clothing , computer science , big data , human body , degree (music) , human body model , body shape , artificial intelligence , data mining , statistics , mathematics , geography , physics , archaeology , acoustics

The existing clothing design model lacks the screening link of the human body part index, and the output clothing data are affected by the high correlation coefficient, resulting in large matching errors. Therefore, based on the analysis of human body shape, a management model of matching degree of human body shape and clothing design based on big data is constructed. After processing with big data methods, human body characteristic data used signals as the input layer of a neural network model and the matching degree management model of human body shape and fashion design. The simulation results show that the built-up model has a matching error of less than 5%, which can effectively improve the matching of human body shape and clothing design.

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