[Retracted] Designing Decorative Flower Patterns for Clothing Using Genetic Algorithm

Abstract

This paper aims to incorporate artistic vocabulary from intangible cultural heritage into historical clothing designs, particularly beautiful pattern designs. It is based on a profound understanding of the concept of immaterial cultural heritage and the mastery of its traditional skills to meet the public’s needs in terms of clothing and flowers. Technology, culture, and intangible cultural legacies can all be passed down and incorporated into the design. It is using interactive evolutionary computing to investigate the intangible cultural heritage elements of designing novel decorative flower patterns for clothing. Due to the rapid advancement of digital technology, computers are now used more frequently in the design of patterns and clothing. The goal is to improve the production of artistic trends and decrease the use of manual and traditional methods. This study uses interactive genetic algorithms to examine the current state of intangible cultural heritage elements in building designs for decorative flower patterns for clothing. The application of genetic algorithms to the design of clothing with flowers as decorative patterns is the main focus of this paper. The genetic algorithm is described, followed by an analysis of its fundamental structure. Then, the characteristics of the clothing flower decorative pattern are determined, the genetic algorithm model is applied to the design of the decorative flower patterns for clothing, and the hierarchical structure of heredity, variation, and interaction is provided. Finally, the genetic algorithm is applied to the large-scale generation and mutation optimization of designing decorative flower patterns for clothing after analyzing its application in clothing flower decorative pattern technology. The idea presented in this paper can self-reproduce and optimize, resulting in the nonartificial generation and optimization of designing decorative flower patterns for clothing.