Risk Evolution Analysis of Cross-Regional Water Diversion Projects Based on Spatio-Temporal Knowledge Graphs
文献类型:期刊论文
作者 | Wang, Lihu7; Liu, Xuemei5,6,7; Dong, Yi3,4; Zhao, Dongxiao2; Wang, Zhenfan2; Chen, Xiaonan1 |
刊名 | JOURNAL OF HYDROLOGY
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出版日期 | 2025-04-01 |
卷号 | 650页码:16 |
关键词 | Cross-regional water diversion projects Spatio-temporal knowledge graphs Risk evolution analysis Complex networks Pre-trained models |
ISSN号 | 0022-1694 |
DOI | 10.1016/j.jhydrol.2024.132533 |
通讯作者 | Liu, Xuemei(liuxuemei@ncwu.edu.cn) |
英文摘要 | The safe operation environment of cross-regional water diversion projects is complex and variable, with risks showing diverse, networked, and dynamic characteristics, posing significant challenges for risk prevention and control. This study attempts to explore the spatio-temporal evolution patterns of coupled risks from a knowledge perspective based on spatio-temporal knowledge graph technology. Incorporating the temporal and spatial dimensions of risk, a risk knowledge extraction method based on pre-trained language models and semantic matching is designed to construct a spatio-temporal knowledge graph. By setting a sliding time window, aggregating identical risks within the window, the spatio-temporal knowledge graph is mapped into a risk evolution network. Investigate the dynamic topological structure of the risk evolution network, and analyze the causal correlations of risks and their evolution patterns in the spatio-temporal dimension. The results indicate that the proposed method achieves high accuracy in risk knowledge extraction (with an average F1 score of 96.65%), the causal correlations of risks significantly influence their spatio-temporal evolution patterns, and the level of causal correlation is positively correlated with the propagation and diffusion of risks. Relevant research can effectively enhance the reliability of engineering management and reduce the impact of potential risks on engineering safety. |
资助项目 | National Natural Science Foundation of China[72271091] ; Projects of Open Cooperation of Henan Academy of Sciences[220901008] ; Major Science and Tech-nology Projects of the Ministry of Water Resources[SKS-2022029] ; Key Research Projects of Higher Education in Henan Province[24A520021] |
WOS研究方向 | Engineering ; Geology ; Water Resources |
语种 | 英语 |
WOS记录号 | WOS:001390795900001 |
出版者 | ELSEVIER |
资助机构 | National Natural Science Foundation of China ; Projects of Open Cooperation of Henan Academy of Sciences ; Major Science and Tech-nology Projects of the Ministry of Water Resources ; Key Research Projects of Higher Education in Henan Province |
源URL | [http://ir.igsnrr.ac.cn/handle/311030/212416] ![]() |
专题 | 中国科学院地理科学与资源研究所 |
通讯作者 | Liu, Xuemei |
作者单位 | 1.China South To North Water Divers Middle Route Cor, Beijing 100032, Peoples R China 2.Yellow River Water & Hydropower Dev Grp Co Ltd, Zhengzhou 450003, Henan, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China 5.North China Univ Water Resources & Elect Power, Collaborat Innovat Ctr Efficient Utilizat Water Re, Zhengzhou 450046, Henan, Peoples R China 6.North China Univ Water Resources & Elect Power, Sch Informat Engn, Zhengzhou 450046, Henan, Peoples R China 7.North China Univ Water Resources & Elect Power, Sch Management & Econ, Zhengzhou 450046, Henan, Peoples R China |
推荐引用方式 GB/T 7714 | Wang, Lihu,Liu, Xuemei,Dong, Yi,et al. Risk Evolution Analysis of Cross-Regional Water Diversion Projects Based on Spatio-Temporal Knowledge Graphs[J]. JOURNAL OF HYDROLOGY,2025,650:16. |
APA | Wang, Lihu,Liu, Xuemei,Dong, Yi,Zhao, Dongxiao,Wang, Zhenfan,&Chen, Xiaonan.(2025).Risk Evolution Analysis of Cross-Regional Water Diversion Projects Based on Spatio-Temporal Knowledge Graphs.JOURNAL OF HYDROLOGY,650,16. |
MLA | Wang, Lihu,et al."Risk Evolution Analysis of Cross-Regional Water Diversion Projects Based on Spatio-Temporal Knowledge Graphs".JOURNAL OF HYDROLOGY 650(2025):16. |
入库方式: OAI收割
来源:地理科学与资源研究所
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