185 related articles for article (PubMed ID: 32886925)
1. Susceptibility mapping and zoning of highway landslide disasters in China.
Yin C; Li H; Che F; Li Y; Hu Z; Liu D
PLoS One; 2020; 15(9):e0235780. PubMed ID: 32886925
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. 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]
4. 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]
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. 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]
7. 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]
8. 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]
9. 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]
10. 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]
11. A hybrid machine learning model for landslide-oriented risk assessment of long-distance pipelines.
Wen H; Liu L; Zhang J; Hu J; Huang X
J Environ Manage; 2023 Sep; 342():118177. PubMed ID: 37210819
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. Seismic landslide susceptibility assessment using principal component analysis and support vector machine.
Xu Z; Che A; Zhou H
Sci Rep; 2024 Feb; 14(1):3734. PubMed ID: 38355620
[TBL] [Abstract][Full Text] [Related]
14. A Robust Deep-Learning Model for Landslide Susceptibility Mapping: A Case Study of Kurdistan Province, Iran.
Ghasemian B; Shahabi H; Shirzadi A; Al-Ansari N; Jaafari A; Kress VR; Geertsema M; Renoud S; Ahmad A
Sensors (Basel); 2022 Feb; 22(4):. PubMed ID: 35214473
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. 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]
17. Hybrid Integration Approach of Entropy with Logistic Regression and Support Vector Machine for Landslide Susceptibility Modeling.
Zhang T; Han L; Chen W; Shahabi H
Entropy (Basel); 2018 Nov; 20(11):. PubMed ID: 33266608
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Landslide Susceptibility Assessment Using Integrated Deep Learning Algorithm along the China-Nepal Highway.
Xiao L; Zhang Y; Peng G
Sensors (Basel); 2018 Dec; 18(12):. PubMed ID: 30558225
[TBL] [Abstract][Full Text] [Related]
20. Evaluation of Different Landslide Susceptibility Models for a Local Scale in the Chitral District, Northern Pakistan.
Aslam B; Maqsoom A; Khalil U; Ghorbanzadeh O; Blaschke T; Farooq D; Tufail RF; Suhail SA; Ghamisi P
Sensors (Basel); 2022 Apr; 22(9):. PubMed ID: 35590797
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
