@article{CHEN2023, 
author = {Shu CHEN and Qin JI and Yun CHEN and Yu LIU and Liping ZHU},
title = {Research progress of smart water conservancy based on knowledge graph},
year = {2023},
journal = {Journal of Hohai University (Natural Sciences)},
volume = {51},
number = {3},
pages = {143-153},
keywords = {smart water conservancy, visual analysis, bibliometrics, co-occurrence cluster analysis, knowledge graph},
url = {https://www.sciopen.com/article/10.3876/j.issn.1000-1980.2023.03.019},
doi = {10.3876/j.issn.1000-1980.2023.03.019},
abstract = {This paper collected relevant research literatures on the smart water conservancy in the databases of China National Knowledge Infrastructure (CNKI) and Web of Science (WOS) from 2000 to 2021. By using the VOSviewer, CiteSpace and other software, this study built various knowledge maps for the time series distribution of literatures in the field of smart water conservancy, publishing institutions, and evolution of research hotspots, to analyze the current progress of smart water conservancy research. The results show that the literature amount of smart water conservancy is increasing year by year, but there is a significant gap between the CNKI database and the WOS database, and core research institutions have been formed in the field of smart water conservancy making important contributions to the frontier development. The CNKI database focuses on the construction of digital watershed and smart water conservancy framework by basin as a unit, while the WOS database focuses on researches from the perspective of geography and earth. Both of them build the platforms for smart water conservancy based on the Internet of Things and deep learning.}
}