The Application of Graph Neural Network and Computer-Aided Design in the Optimization of Architectural Spatial Layout

. In many aspects of architectural design, the optimization of spatial layout is particularly important, as it is directly related to the practicality, comfort, and aesthetics of the building. The objective of this research is to investigate the utilization of graph neural networks (GNN) and computer-aided design (CAD) in refining the layout of architectural spaces. In response to the disorderly expansion in the current building configuration, the development of urbanization has entered a relatively complex relationship. This article introduces a visual quick layout framework for building configurations. Analyzing the inherently complex relationship between GNN and architectural space constructs a visual architectural spatial configuration. Compared with traditional methods, the overall design appears more coherent and efficient. Among different functional requirements, it has higher functional requirements in method layout, which improves the efficiency of architectural design in overall design. In improving the architectural layout of GNN and CAD, the development of urban planning is also reflected differently in the integration of regions.