Classification Of Middle-Aged Women's Body Types In Xinjiang And Prototype Construction

Body type classification has a great impact on clothing plate making and clothing size coverage,and the accuracy of the body type classification method affects the fit of clothing.After entering middle-age women,due to reduced metabolism and fertility,subcutaneous fat continues to accumulate,and Xinjiang is affected by geographical environment and eating habits,resulting in a larger body size of middle-aged women in Xinjiang than in other parts of China,and regional characteristics of body shape obvious.In recent years,some scholars have conducted extensive measurement and body type classification research on different genders and ages in different regions of China,but the research on the body types of middle-aged women in Xinjiang is still at a blank stage.The main research contents of this paper are as follows:(1)In order to avoid the loss of information during principal component analysis or factor analysis,and to improve the scientificity and accuracy of the classification results.This study uses decision tree algorithm to explore body type classification rules,establish a body type recognition model,and solve the problem of body type classification of middle-aged women in Xinjiang.Through the inspection and analysis of the decision tree body type recognition model,it is found that the model is interpretable and robust,and the accuracy rate of the decision tree body type recognition is high through the test set inspection.(2)In order to establish a clothing prototype suitable for middle-aged women in Xinjiang.Regression equations between important characteristic variables are obtained through correlation analysis and linear regression analysis.Based on the Japanese new culture prototype,Liu Ruipu women's clothing prototype,and Donghua prototype,respectively,the clothing prototypes of middle-aged women in Xinjiang have been established.Through virtual fitting evaluation and actual fitting,the experimental prototypes established based on the Donghua prototype and the Liu Ruipu prototype can meet the needs of middle-aged women for clothing comfort and aesthetics.Among them,the experimental prototype established by the Donghua prototype has the best effect.In order to improve the butt-lifting performance of trousers,Taguchi's experimental method was used to optimize the butt-lifting structure of trousers.(3)In order to realize the digital expression of subjective feelings,this paper exploratively uses the LightGBM algorithm to predict the clothing comfort of virtual fittings.The subjective feeling of the actual try-on is used as the label,and the virtual tryon pressure value is the feature,and the structural comfort prediction model of LightGBM clothing is established.Through comparative analysis with random forest and linear regression prediction model,it is found that the prediction model established by LightGBM algorithm is more accurate.