Garment Textile Correction System Based on Artificial Intelligence under Computer Parameter Optimization Design

Abstract

As artificial intelligence technology is widely used in more and more fields, it has become the frontier technology of social innovation. Artificial intelligence based on the development of computer parameters has been widely used in the clothing textile industry, and the technology of the clothing textile correction system has appeared. This article will discuss in detail the development trend of my country’s artificial intelligence technology and the establishment of computer parameters for clothing textiles in combination with the development, model status, and development status of domestic and foreign clothing textiles. Trend and production models will also be developed and analyzed for apparel textile correction system models. The clothing system’s artificial intelligence and production integration, computer parameters, product specifications and other aspects are analyzed. The purpose of this article is to create a clothing textile correction system, which can provide a useful reference for the development of artificial intelligence in the clothing textile industry in our country. Based on relevant knowledge and modern theories in practice, this article is based on a clothing textile correction system using artificial intelligence in computer parameter optimization design. In the course of the experiment, the implementation of the garment textile correction system summarized the technical value and function, as well as the technical purpose and development prospects, through rigorous experiments in theory and practice, to innovate and develop the traditional garment textile production mode. Experimental data shows that under the optimized design of computer parameters, the creation of artificial intelligence-based clothing textile correction system can provide a more convenient way for the clothing textile industry, integrate artificial intelligence into clothing textile production, and improve management efficiency and production efficiency.