Implementation of Art Design Optimization Algorithm Based on Big Data and CAD Technology

Abstract

The core of this study is to use big data (BD) and computer-aided design (CAD) technology to jointly promote innovation in optimization algorithms for art and design, aiming to improve the operational efficiency and visual aesthetics of user interface (UI). To achieve this goal, we conducted an in-depth analysis of the user behaviour and design preferences revealed by BD and utilized the precise modelling ability of CAD technology for targeted design optimization. Through a detailed comparison of new and old user UIs, the results show that the new UI exhibits significant advantages in multiple dimensions. Specifically, when using the new UI, users not only complete tasks faster but also significantly reduce the error rate, resulting in a significant improvement in overall efficiency. Moreover, the new UI has also performed better in colour matching, layout, icon design, and dynamic effect display. These improvements not only optimize the user's operating experience but also make the UI more attractive. Research has shown that art design optimization algorithms based on BD and CAD technologies are practical and feasible. This algorithm not only improves the efficiency of user UI usage but also enhances its visual appeal, which has a positive impact on improving the overall quality and market competitiveness of the product.