AI-driven architectural model family parameter generation method and system
Through the AI-driven architectural model family parameter generation method, family parameters are automatically analyzed and set, which solves the time-consuming and error-prone problems of manual setting, realizes efficient and accurate family parameter setting, and adapts to complex design intentions.
Patent Information
- Application Number
- CN202510932957.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-08
- Publication Date
- 2025-09-05
- Estimated Expiration
- 2045-07-08
AI Technical Summary
In the existing technology, the family parameter setting of building components relies on manual experience, which is time-consuming and labor-intensive and prone to parameter setting errors, affecting the model quality and subsequent applications.
An AI-driven approach is adopted to analyze user design intent through a preset AI large model, break it down into intent points, and automatically map family parameters and parameter value ranges for each intent point. The dependencies and constraints between parameters are considered to avoid contradictory parameter combinations and realize automated family parameter setting.
It improves the accuracy and efficiency of family parameter setting, reduces errors caused by human factors, and optimizes the adaptability of complex design intentions and the parameter determination process.
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Figure CN120449284B_ABST
Abstract
Citation Information
Patent Citations
Fabricated building design and construction integrated collaboration method based on component parameter library
CN115168971A