This invention relates to a method and
system for generating site-specific sustainable architectural design. The method first acquires architectural design text and case images to construct expected and unexpected sample sets. Then, a large
language model is used to process the expected sample set to construct a
knowledge graph for site-specific sustainable architectural design. Simultaneously, expert and public perceptions are extracted from the sample set to generate feature heatmaps. These heatmaps are then analyzed by the large
language model with the
knowledge graph to extract design elements and
design language conducive to site-specific sustainable architectural design, constructing a
knowledge base for site-specific sustainable architectural design. Subsequently, a LoRA model is trained based on this
knowledge base, a supporting prompt word
system is constructed, and an evaluation model is attached to create a knowledge-guided AIGC
workflow for site-specific sustainable architectural design. Finally, the current status image of the target building is input into the
workflow, and the output results are filtered to obtain the site-specific sustainable design scheme for the target building. Compared with existing technologies, this invention has advantages such as improved design generation efficiency and quality.