Fashion Trend Prediction and Clothing Design Optimization Driven by Big Data

With the rapid development of big data technology, its importance in the fashion industry is becoming more and more obvious. Traditional predictions of fashion trends are mainly based on designers' experience and intuition, which are easily limited by personal opinions and lag behind market reactions. Therefore, this paper aims to conduct an indepth study on the application of big data technology in predicting fashion trends and optimizing clothing design to address the inaccuracy and delay of traditional forecasting methods. This paper first outlines the application background and importance of big data research in the fashion industry, then summarizes the research results of relevant scientists on predicting fashion trends based on big data, and points out the gaps in current research. On this basis, a proposed method for predicting fashion trends and optimizing fashion design based on big data is developed, and a fashion design system is constructed. Experimental results show that this method can significantly improve the accuracy of fashion trend prediction, with an accuracy rate of about 95 %, and provide more scientific optimization suggestions for fashion design.