Evolution Path and Application Scenario of Slope Geological Disaster Monitoring--Knowledge Graph Based on Citespace

DOI

10.2991/978-94-6463-336-8_87How to use a DOI?

Keywords

Infrastructure; geological hazards; intelligent algorithm; citespace

Abstract

With the development of global climate change and infrastructure construction, slope geological hazards have become increasingly prominent. Especially for all infrastructure projects with multiple points and line lengths, slope types are complex and diverse, hazard distribution ranges are comprehensive, and influencing factors are diverse. This makes intelligent algorithms increasingly an essential means of efficient research on slope geological hazards. In this paper, Citespace knowledge graph analysis software is used to sort out the CNKI core database from 2000 to 2022. Literature data related to slope geological disaster research based on intelligent algorithms are analyzed through a spatiotemporal evolution map and keyword co-occurrence network to predict the evolution path and research trends and hot spots. The results show that the research on slope geological disasters has experienced four stages: “traditional monitoring -- digital monitoring -- model building --AI collaboration.” The research theme is collected into two spatiotemporal evolution paths with numerical simulation and disaster assessment as the core. The application scenarios mainly include analysis of geological disaster cause mechanisms, geological disaster monitoring methods, and geological disaster prevention exploration. As a result, the field of slope geological hazards will develop towards multi-source data fusion monitoring, multi-disciplinary cross-fusion, and multi-scenario intelligent deduction.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Xiaomin Dai
AU  - Zijie Ye
AU  - Liuyang Xing
AU  - Rong He
AU  - Shengqiang Ma
PY  - 2023
DA  - 2023/12/30
TI  - Evolution Path and Application Scenario of Slope Geological Disaster Monitoring--Knowledge Graph Based on Citespace
BT  - Proceedings of the 2023 9th International Conference on Architectural, Civil and Hydraulic Engineering (ICACHE 2023)
PB  - Atlantis Press
SP  - 769
EP  - 781
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-336-8_87
DO  - 10.2991/978-94-6463-336-8_87
ID  - Dai2023
ER  -