Standout Papers

Machine learning methods for landslide susceptibility studie... 2016 2026 2019 2022 727
  1. Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance (2020)
    Abdelaziz Merghadi, Ali P. Yunus et al. Earth-Science Reviews
  2. A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran (2018)
    Khabat Khosravi, Binh Thai Pham et al. The Science of The Total Environment
  3. A comparative assessment of flood susceptibility modeling using Multi-Criteria Decision-Making Analysis and Machine Learning Methods (2019)
    Khabat Khosravi, Himan Shahabi et al. Journal of Hydrology
  4. Hybrid integration of Multilayer Perceptron Neural Networks and machine learning ensembles for landslide susceptibility assessment at Himalayan area (India) using GIS (2016)
    Binh Thai Pham, Dieu Tien Bui et al. CATENA
  5. A novel hybrid artificial intelligence approach for flood susceptibility assessment (2017)
    Kamran Chapi, Vijay P. Singh et al. Environmental Modelling & Software
  6. Assessment of advanced random forest and decision tree algorithms for modeling rainfall-induced landslide susceptibility in the Izu-Oshima Volcanic Island, Japan (2019)
    Jie Dou, Ali P. Yunus et al. The Science of The Total Environment
  7. A comparative study of different machine learning methods for landslide susceptibility assessment: A case study of Uttarakhand area (India) (2016)
    Binh Thai Pham, Biswajeet Pradhan et al. Environmental Modelling & Software
  8. Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China) (2018)
    Haoyuan Hong, Junzhi Liu et al. CATENA
  9. Improved landslide assessment using support vector machine with bagging, boosting, and stacking ensemble machine learning framework in a mountainous watershed, Japan (2019)
    Jie Dou, Ali P. Yunus et al. Landslides
  10. Influence of Data Splitting on Performance of Machine Learning Models in Prediction of Shear Strength of Soil (2021)
    Quang Hung Nguyen, Hai‐Bang Ly et al. Mathematical Problems in Engineering
  11. Artificial Intelligence Approaches for Prediction of Compressive Strength of Geopolymer Concrete (2019)
    Dong Van Dao, Hai‐Bang Ly et al. Materials
  12. A spatially explicit deep learning neural network model for the prediction of landslide susceptibility (2020)
    Dong Van Dao, Mahmoud Bayat et al. CATENA
  13. Different sampling strategies for predicting landslide susceptibilities are deemed less consequential with deep learning (2020)
    Jie Dou, Ali P. Yunus et al. The Science of The Total Environment
  14. Prediction of ground vibration induced by blasting operations through the use of the Bayesian Network and random forest models (2020)
    Jian Zhou, Panagiotis G. Asteris et al. Soil Dynamics and Earthquake Engineering

Immediate Impact

7 from Science/Nature 63 standout
Sub-graph 1 of 23

Citing Papers

Polyoxometalated metal-organic framework superstructure for stable water oxidation
2025 StandoutScience
MOF-Based Electrocatalysts: An Overview from the Perspective of Structural Design
2025 Standout
2 intermediate papers

Works of Binh Thai Pham being referenced

Bifunctional and binder-free S-doped Ni-P nanospheres electrocatalyst fabricated by pulse electrochemical deposition method for overall water splitting
2020

Author Peers

Author Last Decade Papers Cites
Binh Thai Pham 10832 8439 4466 273 20.9k
Dieu Tien Bui 15524 12916 3949 269 27.9k
Saro Lee 12923 12674 1606 224 20.8k
Wei Chen 9410 8415 1329 183 15.1k
Hamid Reza Pourghasemi 15014 10863 1334 260 23.6k
Himan Shahabi 8824 5791 1147 143 12.9k
Haoyuan Hong 8647 7112 980 99 12.4k
Fausto Guzzetti 12359 21409 3499 206 23.6k
Ian D. Moore 3040 1882 4567 294 13.1k
A‐Xing Zhu 3972 3301 1127 311 11.2k
C.J. van Westen 7291 11760 2169 296 14.9k

All Works

Loading papers...

Rankless by CCL
2026