基于改进启发式搜索算法的区域水资源时空变化特征挖掘方法  

Mining Method of Temporal and Spatial Variation Characteristics of Regional Water Resources Based on Improved Heuristic Search Algorithm

作　　者：胡鑫[1] 刘招雄 HU Xin;LIU Zhaoxiong(Yunnan Provincial Hydrological and Water Resources Bureau Qujing Substation,Qujing 655000,Yunnan,China)

机构地区：[1]云南省水文水资源局曲靖分局,云南曲靖655000

出　　处：《水力发电》2022年第11期32-35,114,共5页Water Power

摘　　要：我国区域水资源时空变化的数据特征较为复杂,特征数据差异化缺少规律,分析特征变化较为困难。为此,提出改进启发式搜索算法的区域水资源时空变化特征挖掘方法。以时空变化的强度和幅度特征作为依据,利用改进启发式搜索算法,筛选出特征明显的数据;围绕着特征数据的使用目的,建立数据仓库;通过抽取、转换等操作处理数据源,划分数据维度,设计逻辑关系,对数据仓库中的数据展开特征挖掘工作,挖掘出有价值的特征数据。实验结果表明,这种数据挖掘方法,针对水资源时空变化特征数据,聚类结果稳定、聚类正确率高。The data characteristics of spatio-temporal changes of regional water resources in China are complex,and the difference of characteristic data is lack of law,so it is difficult to analyze the characteristic changes.An improved heuristic search algorithm is proposed to mine the temporal and spatial variation characteristics of regional water resources.Based on the intensity and amplitude characteristics of spatio-temporal changes,the improved heuristic search algorithm is used to screen out the data with obvious characteristics.Around the purpose of using the characteristic data,the data warehouse is established.Through extraction,transformation and other operations,the data source is processed,the data dimension is divided,the logical relationship is designed,the characteristic mining work is carried out on the data in the data warehouse,and the valuable characteristic data is mined.The experimental results show that this data mining method has stable clustering results and high clustering accuracy for the spatio-temporal change characteristic data of water resources.

关 键 词：信息挖掘 时空特征 区域化 水资源 启发式搜索算法 

分 类 号：TP31[自动化与计算机技术—计算机软件与理论]