Standout Papers
- Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree (2015)
- Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance (2020)
- A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility (2016)
- A comparative assessment of support vector regression, artificial neural networks, and random forests for predicting and mapping soil organic carbon stocks across an Afromontane landscape (2015)
- A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran (2018)
- Hybrid integration of Multilayer Perceptron Neural Networks and machine learning ensembles for landslide susceptibility assessment at Himalayan area (India) using GIS (2016)
- A novel hybrid artificial intelligence approach for flood susceptibility assessment (2017)
- Assessment of advanced random forest and decision tree algorithms for modeling rainfall-induced landslide susceptibility in the Izu-Oshima Volcanic Island, Japan (2019)
- Landslide Susceptibility Assessment in Vietnam Using Support Vector Machines, Decision Tree, and Naïve Bayes Models (2012)
- A comparative study of different machine learning methods for landslide susceptibility assessment: A case study of Uttarakhand area (India) (2016)
- Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China) (2018)
- Improved landslide assessment using support vector machine with bagging, boosting, and stacking ensemble machine learning framework in a mountainous watershed, Japan (2019)
- Spatial prediction of landslide hazard at the Yihuang area (China) using two-class kernel logistic regression, alternating decision tree and support vector machines (2015)
- Comparing the prediction performance of a Deep Learning Neural Network model with conventional machine learning models in landslide susceptibility assessment (2020)
- A hybrid artificial intelligence approach using GIS-based neural-fuzzy inference system and particle swarm optimization for forest fire susceptibility modeling at a tropical area (2016)
- Remote Sensing Approaches for Monitoring Mangrove Species, Structure, and Biomass: Opportunities and Challenges (2019)
Immediate Impact
7 from Science/Nature 155 standout
Citing Papers
Predictive modeling of land surface temperature (LST) based on Landsat-8 satellite data and machine learning models for sustainable development
2024 Standout
A comparative study of explainable ensemble learning and logistic regression for predicting in-hospital mortality in the emergency department
2024 Standout
Works of Dieu Tien Bui being referenced
A tree-based intelligence ensemble approach for spatial prediction of potential groundwater
2020
Improved landslide assessment using support vector machine with bagging, boosting, and stacking ensemble machine learning framework in a mountainous watershed, Japan
2019 Standout
Author Peers
| Author | Last Decade | Papers | Cites | ||||
|---|---|---|---|---|---|---|---|
| Dieu Tien Bui | 15524 | 12916 | 3949 | 6055 | 269 | 27.9k | |
| Saro Lee | 12923 | 12674 | 1606 | 5013 | 224 | 20.8k | |
| Hamid Reza Pourghasemi | 15014 | 10863 | 1334 | 7527 | 260 | 23.6k | |
| Binh Thai Pham | 10832 | 8439 | 4466 | 4263 | 273 | 20.9k | |
| Wei Chen | 9410 | 8415 | 1329 | 3083 | 183 | 15.1k | |
| Biswajeet Pradhan | 31254 | 23823 | 3795 | 13711 | 796 | 54.2k | |
| Himan Shahabi | 8824 | 5791 | 1147 | 3273 | 143 | 12.9k | |
| Haoyuan Hong | 8647 | 7112 | 980 | 2136 | 99 | 12.4k | |
| Fausto Guzzetti | 12359 | 21409 | 3499 | 1168 | 206 | 23.6k | |
| Thomas Blaschke | 9573 | 4544 | 459 | 4952 | 257 | 20.4k | |
| C.J. van Westen | 7291 | 11760 | 2169 | 938 | 296 | 14.9k |
All Works
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