WITHDRAWN: UML diagram classification model based on convolution neural network

Abstract

Nowadays, the amount of data generated daily in various fields is constantly expanding, and the research field of UML diagram is no exception. It has strong expressiveness for complex systems, so it has become the best choice for modeling in many fields. Accordingly, this paper obtains and classifies UML diagram data based on convolution neural network diagram classification algorithm. This paper first analyzes the content and concept of UML, then further describes the importance of building a graphical UML classification model, the complete form convolutional neural network based on image is constructed by analyzing its theory, and then deduces the graphical UML classification model. Finally, a set of UML diagram data set is constructed by using the collected UML diagram design. After data preprocessing, the overall iteration times of the model and the accuracy and average time impact of UML diagram classification model and classification results are obtained. The graph classification algorithm model designed in this study has a good analysis and classification effect for UML object diagrams.Compared with the existing image-based convolutional neural networks and graph neural networks, the proposed UML diagram classification modeling method and GPC-GCN graph neural network have better performance for UML diagram classification. In this study, convolutional neural network technology is applied to the field of UML diagram classification model, thus promoting the development of related technologies in the field of UML diagram classification model.