Research and Intelligent Prediction of Tight-fitting Sportswear Comfort

Abstract Focusing on the mechanism of "human-sport-clothing" system, this paper studies people-oriented sports comfort, and analyzes the influence of different tights combinations (i.e. tights and tights with different fabrics) and the effect of exercise status on the human body parts and overall comfort. In addition, because there are many impact indicators of comfort and the relationship is complicated, it is difficult for general models to deal with this relationship, which leads to the low accuracy of comfort prediction model. To solve this problem, this paper proposes an efficient intelligent prediction model, namely a new hybrid model based on PSO and CS algorithm. The results show that different fabric combinations have significant effects on local and overall comfort under different sports conditions. PSO-CS hybrid model is superior to PSO and CS model in predicting local and global comfort.