136 related articles for article (PubMed ID: 38170358)
1. Dynamic landslide susceptibility mapping based on the PS-InSAR deformation intensity.
Jin B; Zeng T; Yin K; Gui L; Guo Z; Wang T
Environ Sci Pollut Res Int; 2024 Jan; 31(5):7872-7888. PubMed ID: 38170358
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. Landslide Susceptibility Mapping Using Machine Learning Algorithm Validated by Persistent Scatterer In-SAR Technique.
Hussain MA; Chen Z; Zheng Y; Shoaib M; Shah SU; Ali N; Afzal Z
Sensors (Basel); 2022 Apr; 22(9):. PubMed ID: 35590807
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. 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]
6. 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]
7. Combined SBAS-InSAR and PSO-RF Algorithm for Evaluating the Susceptibility Prediction of Landslide in Complex Mountainous Area: A Case Study of Ludian County, China.
Xiao B; Zhao J; Li D; Zhao Z; Zhou D; Xi W; Li Y
Sensors (Basel); 2022 Oct; 22(20):. PubMed ID: 36298394
[TBL] [Abstract][Full Text] [Related]
8. Landslide Susceptibility Mapping with Integrated SBAS-InSAR Technique: A Case Study of Dongchuan District, Yunnan (China).
Zhu Z; Gan S; Yuan X; Zhang J
Sensors (Basel); 2022 Jul; 22(15):. PubMed ID: 35898090
[TBL] [Abstract][Full Text] [Related]
9. Landslide Susceptibility Evaluation Based on Potential Disaster Identification and Ensemble Learning.
Wang X; Zhang X; Bi J; Zhang X; Deng S; Liu Z; Wang L; Guo H
Int J Environ Res Public Health; 2022 Oct; 19(21):. PubMed ID: 36361127
[TBL] [Abstract][Full Text] [Related]
10. Convolutional neural network (CNN) with metaheuristic optimization algorithms for landslide susceptibility mapping in Icheon, South Korea.
Hakim WL; Rezaie F; Nur AS; Panahi M; Khosravi K; Lee CW; Lee S
J Environ Manage; 2022 Mar; 305():114367. PubMed ID: 34968941
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms.
Nhu VH; Shirzadi A; Shahabi H; Singh SK; Al-Ansari N; Clague JJ; Jaafari A; Chen W; Miraki S; Dou J; Luu C; Górski K; Thai Pham B; Nguyen HD; Ahmad BB
Int J Environ Res Public Health; 2020 Apr; 17(8):. PubMed ID: 32316191
[TBL] [Abstract][Full Text] [Related]
13. SBAS-InSAR based validated landslide susceptibility mapping along the Karakoram Highway: a case study of Gilgit-Baltistan, Pakistan.
Kulsoom I; Hua W; Hussain S; Chen Q; Khan G; Shihao D
Sci Rep; 2023 Feb; 13(1):3344. PubMed ID: 36849465
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. 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]
16. Landslide Susceptibility Mapping of Karakorum Highway Combined with the Application of SBAS-InSAR Technology.
Zhao F; Meng X; Zhang Y; Chen G; Su X; Yue D
Sensors (Basel); 2019 Jun; 19(12):. PubMed ID: 31207868
[TBL] [Abstract][Full Text] [Related]
17. A Combination of Geographically Weighted Regression, Particle Swarm Optimization and Support Vector Machine for Landslide Susceptibility Mapping: A Case Study at Wanzhou in the Three Gorges Area, China.
Yu X; Wang Y; Niu R; Hu Y
Int J Environ Res Public Health; 2016 May; 13(5):. PubMed ID: 27187430
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. A novel evolutionary combination of artificial intelligence algorithm and machine learning for landslide susceptibility mapping in the west of Iran.
Shen Y; Ahmadi Dehrashid A; Bahar RA; Moayedi H; Nasrollahizadeh B
Environ Sci Pollut Res Int; 2023 Dec; 30(59):123527-123555. PubMed ID: 37987977
[TBL] [Abstract][Full Text] [Related]
20. Integration of Spatial Probability and Size in Slope-Unit-Based Landslide Susceptibility Assessment: A Case Study.
Li L; Lan H
Int J Environ Res Public Health; 2020 Nov; 17(21):. PubMed ID: 33139639
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
