中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Sensitivity study of multi-field information maps of typical landslides in mining areas based on transfer learning

文献类型:期刊论文

作者Zhang, Yongguo; Yang, Yanzhao; Zhang, Jin; Wang, Yujie
刊名FRONTIERS IN EARTH SCIENCE
出版日期2023-01-24
卷号11
关键词landslide susceptibility zoning transfer learning multi-field information atlas Xishan coal mine area Shanxi Province
DOI10.3389/feart.2023.1105985
文献子类Article
英文摘要The main purpose of this study is to analyze the main influencing factors of the landslide in the coal mine area and, on this basis, establish the sensitivity zoning model of the landslide. Considering the difficulty to obtain the expected results by using machine learning under the condition of lacking data, the typical landslide is used as the data basis, that is, the Fenxi coal mine and Xishan Bujiu coal mine are selected as the coal mining landslide points. Various factors, such as goaf, land subsidence, slope structure, formation lithology, and various indicators are used as input data sources, and artificial neural network (ANN) datasets are used for training to establish a pre-training model. Using the pre-training model, the mining landslide sensitivity evaluation model based on transfer learning is established. In order to demonstrate the performance of transfer learning more intuitively, the neural network is introduced to evaluate the evaluation model. The test results show that transfer learning can achieve a transfer effect higher than 0.95, and the regional distributions of highest landslide sensitivity calculated based on self-transfer learning, direct push transfer learning, and inductive transfer learning are 31.33, 35.50, and 33.75%, respectively, which further deduced that inductive transfer learning can be used for evaluating an LSP model.
WOS关键词UNCERTAINTY ; MODEL
WOS研究方向Geology
出版者FRONTIERS MEDIA SA
WOS记录号WOS:000927029600001
源URL[http://ir.igsnrr.ac.cn/handle/311030/189634]  
专题资源利用与环境修复重点实验室_外文论文
作者单位1.Institute of Geographic Sciences & Natural Resources Research, CAS
2.Chinese Academy of Sciences
3.Taiyuan University of Technology
推荐引用方式
GB/T 7714
Zhang, Yongguo,Yang, Yanzhao,Zhang, Jin,et al. Sensitivity study of multi-field information maps of typical landslides in mining areas based on transfer learning[J]. FRONTIERS IN EARTH SCIENCE,2023,11.
APA Zhang, Yongguo,Yang, Yanzhao,Zhang, Jin,&Wang, Yujie.(2023).Sensitivity study of multi-field information maps of typical landslides in mining areas based on transfer learning.FRONTIERS IN EARTH SCIENCE,11.
MLA Zhang, Yongguo,et al."Sensitivity study of multi-field information maps of typical landslides in mining areas based on transfer learning".FRONTIERS IN EARTH SCIENCE 11(2023).

入库方式: OAI收割

来源:地理科学与资源研究所

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