基于工业互联网知识图谱的风景园林生态规划决策方法
By using a closed-loop decision-making framework based on industrial internet knowledge graphs, the problems of real-time perception, data fusion, quantification of association rules, dynamic inference, and scenario-based decision-making in traditional landscape architecture ecological planning are solved, enabling real-time dynamic optimization and improved adaptability of planning schemes.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- MIANYANG TEACHERS COLLEGE
- Filing Date
- 2026-04-08
- Publication Date
- 2026-07-17
AI Technical Summary
Traditional landscape architecture ecological planning methods lack real-time sensing capabilities, cannot integrate multi-source heterogeneous data, are qualitative in ecological correlation analysis, lack real-time planning and simulation, have a single decision-making model, insufficient verification of the adaptability of industrial sensing networks, and lack iterative implementation, resulting in deviations between planning schemes and actual ecological conditions, insufficient adaptability, and inability to dynamically optimize.
Based on the Industrial Internet knowledge graph, a closed-loop decision-making framework is constructed that covers the entire process of perception, adaptation, modeling, mining, inference, decision-making, and iteration. Through the Industrial Internet perception network, knowledge graph, and edge-cloud collaboration technology, the framework achieves real-time data processing, quantitative correlation, dynamic inference, scenario-based decision-making, and iterative implementation. HIN2Vec, TAMP, GraphWave, and FedDyn algorithms are used for data processing and inference.
It has enabled real-time data processing, quantitative correlation, dynamic simulation, scenario-based decision-making, and iterative implementation for landscape architecture and ecological planning, improving the adaptability and scientific nature of planning schemes, reducing implementation and operation and maintenance costs, and forming a closed-loop decision-making process.
Smart Images
Figure CN122022190B_ABST