Evaluation of Modeling Strategies for Fashion Design Process Based on DCGAN Algorithm

With the development of The Times, there are more and more types and patterns of fashion design, and people have more and more choices to buy clothes. However, among the increasing number of clothes, there are some poor quality clothes, so how to further improve the quality of clothes is very important. This paper studies the modeling strategy analysis of the clothing design process based on the DCGAN (Deep Convolution Adversarial Networks) algorithm. That is, the clothing design process is modeled through the DCGAN algorithm, and then the optimal design scheme is obtained. In this paper, the maximum fit of clothing using DCGAN algorithm is 93% and the minimum is 80%, while the maximum fit of traditional clothing is 75% and the minimum is 68%. Through this experimental data, it can be seen that DCGAN algorithm has a good effect on clothing design and has a high degree of fit with clothing design.