The evolution of Chinese traditional ethnic clothing design style based on interactive dichroism algorithm

Abstract

In this paper, a traditional ethnic clothing design style model is proposed, aiming to promote the good development of clothing in artificial intelligence design. The model uses an interactive dichotomous meter algorithm for top-down information gain, differentiates sample attributes by selecting entropy values, and defines an average categorical fuzzy subset based on discrete attribute leaf node division for deep, circular arithmetic decision-making. After satisfying the clothing design evolution condition, the minimum prediction entropy value genus block is extended, and the feedback matrix random input variables are used to induce the regularized likelihood frequency classification value distribution. The results of the analysis of traditional ethnic clothing design show that there are {0, 0.5, 1} mathematical expressions on clothing design hues, the demand of clothing design value subject shows a positive state, the change of consumption wave that festival and style will bring, the knowledge value in the mean difference of clothing design orientation is as high as 0.9173 with a significant value of 0.00<0.05. Therefore, the design style of traditional ethnic clothing is not only the inheritance and promotion of national culture but also the enhancement and development of aesthetic consciousness.

Keywords

• clothing design style
• dichotomous meter algorithm
• information gain
• discrete attributes
• classification fuzziness
• regularization possibility
• 65d17