| 甘甜,王超,蒋云钟,韩昆.基于时空动态知识图谱的明渠实时调度模式智能识别研究[J].水利学报,2025,56(5):646-658 |
| 基于时空动态知识图谱的明渠实时调度模式智能识别研究 |
| Intelligent identification of real-time regulation pattern in open channels based on spatiotemporal dynamic knowledge graph |
| 投稿时间：2024-09-18 |
| DOI：10.13243/j.cnki.slxb.20240597 |
| 中文关键词: 知识图谱 时空动态 明渠实时调度 调度模式识别 |
| 英文关键词: knowledge graph spatiotemporal dynamics real time regulation of open channels regulation pattern recognition |
| 基金项目:国家自然科学基金项目（52394234）；国家重点研发计划课题（2022YFC3204603）；水利部重大科技项目（SKS-2022117，SKR-2022057） |
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| 中文摘要: |
| 根据明渠水力特征与工程实际需求，进行实时智能调度模式识别，能为工程管理提供决策辅助，提高调水工程智能化水平。本研究针对明渠实时调度相关要素多、关系复杂、时变性强，导致调度模式识别效率低的问题，以胶东调水工程王耨-入吴沟河段为典型渠段，构建了描述明渠水力特征时空动态变化的知识图谱。首先利用HEC-RAS软件进行历史场景模拟分析，获得不同调度模式下满足各自调度目标的优选闸门开度初始值与闸门开度调节趋势等先验知识；然后基于密度聚类-随机森林（DBSCAN-RF）分类算法进行历史场景分类分析，得到带标签的分类样本集；最后利用Neo4j图数据库结构化存储历史场景特征及模拟与分类知识，形成时空动态图谱，最终实现明渠实时调度模式的智能识别。 |
| 英文摘要: |
| Based on the hydraulic characteristics of open channels and the actual demand of engineering projects，real-time pattern recognition for intelligent regulation can provide decision-making support for engineering management，thus enhancing the intelligent level of water transfer projects. This study，aiming at the problem of low efficiency in regulation pattern recognition due to the numerous related elements，complex relationships，and strong time-varying nature of real-time open channel regulation，constructs a knowledge graph that describes the spatiotem poral dynamic changes of the hydraulic characteristics of open channels，using the Wangnou-Ruwugou river section of the Jiaodong Water Transfer Project as an example. Firstly，HEC-RAS software was utilized for historical scenario simulation analysis to obtain prior knowledge，such as optimal initial gate opening values and gate opening adjustment trends under different regulation patterns that meet their respective regulation objectives. Then，based on the Density-Based Spatial Clustering of Applications with Noise-Random Forest （DBSCAN-RF） classification algorithm，historical scenario classification analysis was conducted to obtain a labeled classification sample set. Finally，the Neo4j graph database was used to structurally store historical scenario characteristics and simulation and classification knowledge，forming a spatiotemporal dynamic atlas，ultimately achieving intelligent recognition of real-time scheduling patterns for open channels. |
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