需水量预测技术方法文献分析及其应用综述  

Review and Bibliometrics Analysis of Prediction Technology and Method of Water Demand

作　　者：栾清华[1,2] 庞婷婷[1] 王志友 高昊悦 何立新 何帅[1] 董森[1] LUAN Qinghua;PANG Tingting;WANG Zhiyou;GAO Haoyue;HE Lixin;HE Shuai;DONG Sen(Hebei Key Laboratory of Intelligent Water Conservancy,Hebei University of Engineering,Handan 056038,China;College of Agricultural Science and Engineering,Hohai University,Nanjing 210098,China;Hebei Water Resources Research and Water Conservancy Technology Test and Extension Center,Shijiazhuang 050072,China)

机构地区：[1]河北工程大学河北省智慧水利重点实验室,河北邯郸056038 [2]河海大学农业科学与工程学院,江苏南京210098 [3]河北省水资源研究与水利技术试验推广中心,河北石家庄050072

出　　处：《人民黄河》2022年第12期62-66,共5页Yellow River

基　　金：国家自然科学基金面上项目(51879066);国家重点研发计划项目(2016YFC0401404)。

摘　　要：准确的需水量预测是合理分配水资源、促进水资源合理开发利用的基础。为了解国内外需水量预测技术应用现状,利用知识图谱可视化软件VOSviewer,对2000—2021年需水量预测研究文献关键词进行可视化分析,分类归纳并对比分析了常用方法的适用性、局限性以及在我国不同行业中的应用情况。结果表明:人工神经网络法、回归分析法、灰色预测法是国内外经济社会需水量预测研究中常用的技术方法;需水定额法与人工神经网络法、回归分析法、灰色预测法是国内具有关联性的常用方法;各类方法在行业需水研究中均有其优势和局限性,人工神经网络和灰色理论及其改进耦合模型的研究较多,定额法在应用研究和实际管理中多被采用。未来随着大数据和智能算法的广泛应用,应优化数学模型参数和需水定额,以提高需水量预测的准确性。Accurate water demand prediction is the basis for reasonable water resources development and utilization.According to the biblio⁃metrics analysis on water demand prediction in the recent 22 years through VOSviewer,the applicabilities and limitations of normal methods were classified and compared and the related application of each method in different industries was listed.The results show that the artificial neural network,regression analysis and grey prediction are frequently applied in the domestic and abroad researches;the water quota method has a correlation with artificial neural network,regression analysis and grey prediction.Each method has its advantages and limitations in practical application.The artificial neural network,grey model and their improved coupling model are frequently studied and the quota meth⁃od is mostly utilized in practical research and management.In the future,with the widespread utilization of the intelligent algorithm and big data,the mathematics model parameters and water use quotas should be optimized to improve the accuracy of water demand prediction.

关 键 词：需水量预测 预测方法 行业需水 文献计量分析 VOSviewer 

分 类 号：TV213.9[水利工程—水文学及水资源]