| Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance A Merghadi, AP Yunus, J Dou, J Whiteley, B ThaiPham, DT Bui, R Avtar, ... Earth-Science Reviews 207, 103225, 2020 | 821 | 2020 |
| Hybrid integration of Multilayer Perceptron Neural Networks and machine learning ensembles for landslide susceptibility assessment at Himalayan area (India) using GIS BT Pham, DT Bui, I Prakash, MB Dholakia Catena 149, 52-63, 2017 | 627 | 2017 |
| A novel hybrid artificial intelligence approach for flood susceptibility assessment K Chapi, VP Singh, A Shirzadi, H Shahabi, DT Bui, BT Pham, K Khosravi Environmental modelling & software 95, 229-245, 2017 | 592 | 2017 |
| A comparative study of different machine learning methods for landslide susceptibility assessment: A case study of Uttarakhand area (India) BT Pham, B Pradhan, DT Bui, I Prakash, MB Dholakia Environmental Modelling & Software 84, 240-250, 2016 | 530 | 2016 |
| Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China) H Hong, J Liu, DT Bui, B Pradhan, TD Acharya, BT Pham, AX Zhu, ... Catena 163, 399-413, 2018 | 480 | 2018 |
| Landslide susceptibility assesssment in the Uttarakhand area (India) using GIS: a comparison study of prediction capability of naïve bayes, multilayer perceptron neural … BT Pham, D Tien Bui, HR Pourghasemi, P Indra, MB Dholakia Theoretical and Applied Climatology 128 (1), 255-273, 2017 | 382 | 2017 |
| Development of advanced artificial intelligence models for daily rainfall prediction BT Pham, LM Le, TT Le, KTT Bui, VM Le, HB Ly, I Prakash Atmospheric Research 237, 104845, 2020 | 228 | 2020 |
| A hybrid machine learning ensemble approach based on a radial basis function neural network and rotation forest for landslide susceptibility modeling: A case study in the … BT Pham, A Shirzadi, DT Bui, I Prakash, MB Dholakia International Journal of Sediment Research 33 (2), 157-170, 2018 | 177 | 2018 |
| Flood risk assessment using hybrid artificial intelligence models integrated with multi-criteria decision analysis in Quang Nam Province, Vietnam BT Pham, C Luu, T Van Phong, HD Nguyen, H Van Le, TQ Tran, HT Ta, ... Journal of Hydrology 592, 125815, 2021 | 175 | 2021 |
| A comparative study of least square support vector machines and multiclass alternating decision trees for spatial prediction of rainfall-induced landslides in a tropical … BT Pham, D Tien Bui, MB Dholakia, I Prakash, HV Pham Geotechnical and Geological Engineering 34 (6), 1807-1824, 2016 | 168 | 2016 |
| Rotation forest fuzzy rule-based classifier ensemble for spatial prediction of landslides using GIS BT Pham, D Tien Bui, I Prakash, MB Dholakia Natural Hazards 83 (1), 97-127, 2016 | 154 | 2016 |
| Landslide susceptibility assessment using bagging ensemble based alternating decision trees, logistic regression and J48 decision trees methods: a comparative study BT Pham, D Tien Bui, I Prakash Geotechnical and Geological Engineering 35 (6), 2597-2611, 2017 | 134 | 2017 |
| A comparative study between popular statistical and machine learning methods for simulating volume of landslides A Shirzadi, H Shahabi, K Chapi, DT Bui, BT Pham, K Shahedi, BB Ahmad Catena 157, 213-226, 2017 | 119 | 2017 |
| Flood risk assessment using deep learning integrated with multi-criteria decision analysis BT Pham, C Luu, D Van Dao, T Van Phong, HD Nguyen, H Van Le, ... Knowledge-based systems 219, 106899, 2021 | 118 | 2021 |
| A comparison of Support Vector Machines and Bayesian algorithms for landslide susceptibility modelling BT Pham, I Prakash, K Khosravi, K Chapi, PT Trinh, TQ Ngo, SV Hosseini, ... Geocarto International 34 (13), 1385-1407, 2019 | 116 | 2019 |
| Estimation of axial load-carrying capacity of concrete-filled steel tubes using surrogate models HB Ly, BT Pham, LM Le, TT Le, VM Le, PG Asteris Neural Computing and Applications 33 (8), 3437-3458, 2021 | 113 | 2021 |
| Application and comparison of decision tree-based machine learning methods in landside susceptibility assessment at Pauri Garhwal Area, Uttarakhand, India BT Pham, K Khosravi, I Prakash Environmental Processes 4 (3), 711-730, 2017 | 111 | 2017 |
| Can deep learning algorithms outperform benchmark machine learning algorithms in flood susceptibility modeling? BT Pham, C Luu, T Van Phong, PT Trinh, A Shirzadi, S Renoud, S Asadi, ... Journal of hydrology 592, 125615, 2021 | 109 | 2021 |
| Metaheuristic optimization of Levenberg–Marquardt-based artificial neural network using particle swarm optimization for prediction of foamed concrete compressive strength HB Ly, MH Nguyen, BT Pham Neural Computing and Applications 33 (24), 17331-17351, 2021 | 100 | 2021 |
| Improved flood susceptibility mapping using a best first decision tree integrated with ensemble learning techniques BT Pham, A Jaafari, T Van Phong, HPH Yen, TT Tuyen, V Van Luong, ... Geoscience Frontiers 12 (3), 101105, 2021 | 99 | 2021 |
Indra PrakashGeological Survey of India, Dy.DG(R), Collaborative ResearcherZweryfikowany adres z bisag.gujarat.gov.in