Optimization of Dynamic Graphic Packaging Design Scheme Based on Graph Neural Network

• Published in: Mobile information systems 2022-07, Vol.2022, p.1-10
• Main Author: Tao, Jie
• Format: Article
• Language: English
• Subjects: Algorithms; Behavior; Design; Design optimization; Eigenvalues; Eye movements; Graph neural networks; Memory; Methods; Neural networks; Optimization; Package design; Packaging; Packaging design; Visual communication
• ISSN: 1574-017X; 1875-905X
• DOI: 10.1155/2022/5075884

The traditional packaging design is inseparable from graphics, but the graphics is static, and the emergence of dynamic graphics breaks the conventional packaging design concept. This study optimized dynamic graph packaging design based on graph neural network technology. This paper first gives a brief introduction to the graph neural network, mainly to optimize the problem that the graph neural network has a large number of learning, and also expounds the principle of the graph neural network using formulas. Then this paper introduces the dynamic graphic packaging design in detail, which involves the elements of packaging design, the types of dynamic graphics, design ideas, and so on. Later, this paper tests users’ attention to the product through eye movement experiment and graph neural network algorithm. The experiment showed that the dynamic graphics packaging design of product 7 was the most popular, with the dynamic graphics area users viewed it up to 93 times. It can be seen that this dynamic graphic packaging design optimization scheme is effective, and it also provides a possibility for the optimization of dynamic graphic packaging design scheme.