Shear wall structures are widely used in high-rise residential buildings, and the layout of shear walls requires many years of design experience and iterative trial and error. Currently, there are methods based on heuristic algorithms, but they generate results too slowly. Those based on Generative Adversarial Networks (GANs) or Graph Neural Networks (GNNs) can only generate single arrangements and require large amounts of training data. At present, Stable Diffusion is being widely used, and by using the Low-Rank Adaptation (LoRA) method to fine-tune large models with small amounts of data, good generative results can be achieved. Therefore, this paper proposes a personalized AI assistant for shear wall layout based on Stable Diffusion, which has been proven to produce good generative results through testing.

翻译：剪力墙结构广泛应用于高层住宅建筑中，其布局设计需要多年的设计经验与反复试错。当前存在基于启发式算法的方法，但生成速度过慢；基于生成对抗网络（GANs）或图神经网络（GNNs）的方法虽能生成单一布局，但需要大量训练数据。目前稳定扩散技术正被广泛使用，通过低秩适配（LoRA）方法以少量数据微调大模型即可获得良好的生成效果。为此，本文提出了一种基于稳定扩散的剪力墙布局个性化人工智能助手，经测试证明其能产生优异布局结果。