一种基于AI算法的BIM模型智能化创建方法及系统
By optimizing the BIM model construction method through AI algorithms and combining graph neural networks and reinforcement learning, the problem of low automation in BIM models has been solved, enabling efficient identification of component conflicts and missing parts, and improving the intelligence and adaptability of the model.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- LONG TECH CO LTD
- Filing Date
- 2025-06-10
- Publication Date
- 2026-07-17
AI Technical Summary
Existing BIM model building methods have low automation, inaccurate identification of component spatial conflicts, difficulty in intelligent optimization, lack of end-to-end learning and generalization capabilities, and inability to adapt to dynamically changing layout schemes.
An AI-based approach is employed to parse CAD drawings using the Revit API, generate particle coordinates, and calculate multi-objective costs. Graph neural networks and reinforcement learning strategies are used to optimize component positions, and convolutional neural networks are combined to detect conflicts and missing data. A real-time data stream platform is then built for automatic updates.
It enables efficient identification of component conflicts and missing parts, improves the intelligence level of BIM modeling, enhances the model's adaptability and generalization ability, and significantly improves the rationality and constructability of component layout.
Smart Images
Figure CN120654303B_ABST