These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
133 related articles for article (PubMed ID: 38146028)
1. GIS-based landslide susceptibility zoning using a coupled model: a case study in Badong County, China. Wang P; Deng H; Liu Y Environ Sci Pollut Res Int; 2024 Jan; 31(4):6213-6231. PubMed ID: 38146028 [TBL] [Abstract][Full Text] [Related]
2. Refined Zoning of Landslide Susceptibility: A Case Study in Enshi County, Hubei, China. Wang Z; Ma C; Qiu Y; Xiong H; Li M Int J Environ Res Public Health; 2022 Aug; 19(15):. PubMed ID: 35954770 [TBL] [Abstract][Full Text] [Related]
3. Comparison of Random Forest Model and Frequency Ratio Model for Landslide Susceptibility Mapping (LSM) in Yunyang County (Chongqing, China). Wang Y; Sun D; Wen H; Zhang H; Zhang F Int J Environ Res Public Health; 2020 Jun; 17(12):. PubMed ID: 32545618 [TBL] [Abstract][Full Text] [Related]
4. Exploring machine learning and statistical approach techniques for landslide susceptibility mapping in Siwalik Himalayan Region using geospatial technology. Saha A; Tripathi L; Villuri VGK; Bhardwaj A Environ Sci Pollut Res Int; 2024 Feb; 31(7):10443-10459. PubMed ID: 38198087 [TBL] [Abstract][Full Text] [Related]
5. Evaluation of Landslide Susceptibility Based on CF-SVM in Nujiang Prefecture. Li Y; Deng X; Ji P; Yang Y; Jiang W; Zhao Z Int J Environ Res Public Health; 2022 Oct; 19(21):. PubMed ID: 36361126 [TBL] [Abstract][Full Text] [Related]
6. A landslide susceptibility map based on spatial scale segmentation: A case study at Zigui-Badong in the Three Gorges Reservoir Area, China. Yu X; Gao H PLoS One; 2020; 15(3):e0229818. PubMed ID: 32160206 [TBL] [Abstract][Full Text] [Related]
7. GIS-based landslide susceptibility mapping in the Longmen Mountain area (China) using three different machine learning algorithms and their comparison. Huang Z; Peng L; Li S; Liu Y; Zhou S Environ Sci Pollut Res Int; 2023 Aug; 30(38):88612-88626. PubMed ID: 37440134 [TBL] [Abstract][Full Text] [Related]
8. Landslide Susceptibility Evaluation Using Different Slope Units Based on BP Neural Network. Huang J; Zeng X; Ding L; Yin Y; Li Y Comput Intell Neurosci; 2022; 2022():9923775. PubMed ID: 35655489 [TBL] [Abstract][Full Text] [Related]
9. Landslide Susceptibility Evaluation of Machine Learning Based on Information Volume and Frequency Ratio: A Case Study of Weixin County, China. He W; Chen G; Zhao J; Lin Y; Qin B; Yao W; Cao Q Sensors (Basel); 2023 Feb; 23(5):. PubMed ID: 36904752 [TBL] [Abstract][Full Text] [Related]
10. Zonation of Landslide Susceptibility in Ruijin, Jiangxi, China. Zhou X; Wu W; Lin Z; Zhang G; Chen R; Song Y; Wang Z; Lang T; Qin Y; Ou P; Huangfu W; Zhang Y; Xie L; Huang X; Fu X; Li J; Jiang J; Zhang M; Liu Y; Peng S; Shao C; Bai Y; Zhang X; Liu X; Liu W Int J Environ Res Public Health; 2021 May; 18(11):. PubMed ID: 34072874 [TBL] [Abstract][Full Text] [Related]
11. Optimizing the Predictive Ability of Machine Learning Methods for Landslide Susceptibility Mapping Using SMOTE for Lishui City in Zhejiang Province, China. Wang Y; Wu X; Chen Z; Ren F; Feng L; Du Q Int J Environ Res Public Health; 2019 Jan; 16(3):. PubMed ID: 30696105 [TBL] [Abstract][Full Text] [Related]
12. Mine landslide susceptibility assessment using IVM, ANN and SVM models considering the contribution of affecting factors. Luo X; Lin F; Zhu S; Yu M; Zhang Z; Meng L; Peng J PLoS One; 2019; 14(4):e0215134. PubMed ID: 30973936 [TBL] [Abstract][Full Text] [Related]
13. Optimization of Causative Factors for Landslide Susceptibility Evaluation Using Remote Sensing and GIS Data in Parts of Niigata, Japan. Dou J; Tien Bui D; Yunus AP; Jia K; Song X; Revhaug I; Xia H; Zhu Z PLoS One; 2015; 10(7):e0133262. PubMed ID: 26214691 [TBL] [Abstract][Full Text] [Related]
14. Evaluation of landslides susceptibility in Southeastern Tibet considering seismic sensitivity. Yeqi Z; Yonggang G; Guowen W; Shengjie W Heliyon; 2024 Sep; 10(18):e36800. PubMed ID: 39309935 [TBL] [Abstract][Full Text] [Related]
15. Integrating stratified best-worst method and GIS for landslide susceptibility assessment: a case study in Erzurum province (Turkey). Konurhan Z; Yucesan M; Gul M Environ Sci Pollut Res Int; 2023 Nov; 30(53):113978-114000. PubMed ID: 37858024 [TBL] [Abstract][Full Text] [Related]
16. Slide type landslide susceptibility assessment of the Büyük Menderes watershed using artificial neural network method. Tekin S; Çan T Environ Sci Pollut Res Int; 2022 Jul; 29(31):47174-47188. PubMed ID: 35178630 [TBL] [Abstract][Full Text] [Related]
17. Assessment of Landslide Susceptibility Based on Multiresolution Image Segmentation and Geological Factor Ratings. Duan G; Zhang J; Zhang S Int J Environ Res Public Health; 2020 Oct; 17(21):. PubMed ID: 33120996 [TBL] [Abstract][Full Text] [Related]
18. Application of Bagging, Boosting and Stacking Ensemble and EasyEnsemble Methods for Landslide Susceptibility Mapping in the Three Gorges Reservoir Area of China. Wu X; Wang J Int J Environ Res Public Health; 2023 Mar; 20(6):. PubMed ID: 36981886 [TBL] [Abstract][Full Text] [Related]
19. Landslide Susceptibility Assessment Using Spatial Multi-Criteria Evaluation Model in Rwanda. Nsengiyumva JB; Luo G; Nahayo L; Huang X; Cai P Int J Environ Res Public Health; 2018 Jan; 15(2):. PubMed ID: 29385096 [TBL] [Abstract][Full Text] [Related]
20. Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China. Chen W; Peng J; Hong H; Shahabi H; Pradhan B; Liu J; Zhu AX; Pei X; Duan Z Sci Total Environ; 2018 Jun; 626():1121-1135. PubMed ID: 29898519 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]