基于知识-数据驱动的河网水闸智能运行研究  

Research on Intelligent Operation of River Network Sluices based on Knowledge-Data Driven Approach

作　　者：张立超 Zhang Lichao(Guzhen County Huaihong New River Course Management Bureau Anhui Province,Bengbu 233700,China)

机构地区：[1]安徽省怀洪新河固镇县河道管理局,安徽蚌埠233700

出　　处：《黑龙江水利科技》2025年第3期47-53,共7页Heilongjiang Hydraulic Science and Technology

摘　　要：文章提出了一种融合知识驱动与数据驱动机制的河网水闸运行规则优化方法,以应对复杂的水文条件和多变的河网环境。通过构建河网数学模型(RNMM)、快速模拟模型(RSM)以及运筹规则优化模型(OROM),实现了水闸运行规则的智能优化。以上海市浦东新区潮汐河网为例,通过多个典型水资源调度案例的仿真与优化,验证了该方法的有效性和适用性。研究结果表明,该优化方法能显著提高水资源利用效率,改善河网水质,并增强防洪能力。RSM显著提升了计算效率,且保证了预测精度,遗传算法(GA)在复杂的多目标优化中展现出优异的全局搜索能力。此外,参数配置对优化结果有重要影响,通过合理调整流量上限和权重参数,可在多重目标之间实现有效平衡。文章为复杂河网系统的水资源管理提供了一种科学、系统的解决方案,具有重要的理论与实践价值。In this paper,a knowledge-driven and data-driven optimization method for river network sluice operation rules is proposed to cope with complex hydrological conditions and variable river network environment.By constructing a River Network Mathematical Model(RNMM),a Rapid Simulation Model(RSM),and an Operation Rule Optimization Model(OROM),intelligent optimization of sluice operation rules is achieved.Using the tidal river network in Pudong New Area,Shanghai as a case study,the effectiveness and applicability of the proposed method were validated through the simulation and optimization of several typical water resource scheduling cases.The results show that this optimization method significantly improves water resource utilization efficiency,enhances river network water quality,and strengthens flood control capabilities.The introduction of RSM greatly improves computational efficiency while ensuring prediction accuracy,the Genetic Algorithm(GA)demonstrates excellent global search capabilities in complex multi-objective optimization problems.Additionally,parameter configuration has a significant impact on optimization results,and by reasonably adjusting the upper flow limits and weight parameters,an effective balance among multiple objectives can be achieved.This study provides a scientific and systematic solution for water resource management in complex river network systems,offering significant theoretical and practical value.

关 键 词：河网水闸 智能优化 知识驱动 数据驱动 遗传算法 快速模拟模型 

分 类 号：TV66[水利工程—水利水电工程]