摘要
为了解决水资源承载力影响因素的复杂性问题,引入知识图谱技术,以海量研究成果作为数据源,通过知识抽取建立指标实体集合、耦合熵值和变差系数增强指标的代表性、基于最大信息系数的知识合并减少指标的交叉和重复、运用灰色关联的知识推理遴选关键指标,最后基于专家咨询形成高质量知识并应用Neo4j图数据库对实体、关系、属性等指标知识进行存储与服务。这种基于知识图谱所构建的指标体系不仅知识性强,而且系统全面,较好地解决了水资源承载力影响因素复杂性建模问题,为水资源承载力评价指标体系构建提供了一种新方法。
In order to solve the complexity problem of water resources carrying capacity influencing factors,this paper introduces knowledge graph technology and takes massive research results as data sources.The indicator entities set is established through knowledge extraction.Entropy value and variation coefficient is coupled to enhance the representativeness of indicators.Knowledge merging based on the maximum information coefficient reduces the crossover and duplication of indicators.Grey correlation knowledge reasoning is used to select the key indicators.Finally,high-quality knowledge based on expert consultation is formed and the indicator knowledge such as entities,relationships,and attributes is stored using the Neo4j graph database.This indicator system based on knowledge graph is not only knowledgeable,but also comprehensive,which solves the problem of complex modeling of influencing factors of water carrying capacity,and provides a new method for the construction of water resource carrying capacity evaluation indicator system.
作者
任娟慧
任波
李慧姝
REN Juan-hui;REN Bo;LI Hui-shu(College of Electrical and Power Engineering,Taiyuan University of Technology,Taiyuan 030024,China;Hydrology Station of Shanxi Province,Taiyuan 030001,China;Shanxi Institute of Energy,Jinzhong 030600,China)
出处
《水电能源科学》
北大核心
2024年第8期53-56,47,共5页
Water Resources and Power
基金
山西省重点研发项目(202202020101007)。
关键词
水资源承载力
知识图谱
评价指标体系
方法
water resources carrying capacity
knowledge graph
evaluation indicator system
method
