基于K-medoids聚类处理的梯级水利枢纽信息智能整合方法  

Intelligent integration method of cascade water conservancy hub information based on K⁃medoids clustering processing

作　　者：亓振涛 QI Zhentao(Beijing Antaitong Automation Technology Co.,Ltd.,Beijing 100080,China)

机构地区：[1]北京市安太通自动化技术有限公司,北京100080

出　　处：《电子设计工程》2025年第3期13-17,23,共6页Electronic Design Engineering

摘　　要：为了提高梯级水利枢纽信息在实际工作中的利用率,提出基于K-medoids聚类处理的梯级水利枢纽信息智能整合方法。从项目信息、水文、枢纽设备等方面,采集梯级水利枢纽信息,针对不同信息类型通过清洗、归一化等步骤,完成初始信息的预处理。以梯级水利枢纽信息特征的提取结果为处理对象,利用K-medoids处理技术完成梯级水利枢纽信息的聚类,通过整合信息的冗余过滤,得出信息智能整合结果。通过性能测试实验得出结论:与传统整合方法相比,优化方法的完整度提高了6.06%、冗余度降低了1.79%,同时整合信息具有更高的利用率。In order to improve the utilization rate of cascade water conservancy hub information in practical work,an intelligent integration method for cascade water conservancy hub information based on K⁃medoids clustering processing is proposed.Collect information on cascade water conservancy hubs from aspects such as project information,hydrology,and hub equipment,and complete initial information preprocessing through steps such as cleaning and normalization for different types of information.Taking the extraction results of information features of cascade water conservancy hubs as the processing object,K⁃medoids processing technology is used to cluster the information of cascade water conservancy hubs.Through redundant filtering of integrated information,the intelligent integration result of information is obtained.The conclusion drawn from performance testing experiments is that compared with traditional integration methods,the optimized method has improved completeness by 6.06%,reduced redundancy by 1.79%,and integrated information has a higher utilization rate.

关 键 词：K-medoids聚类处理技术 梯级水利枢纽 水利信息 信息整合 

分 类 号：TN0[电子电信—物理电子学]