| 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 | 256 | 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 | 232 | 2016 |
| A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran K Khosravi, BT Pham, K Chapi, A Shirzadi, H Shahabi, I Revhaug, ... Science of the Total Environment 627, 744-755, 2018 | 222 | 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, DT Bui, HR Pourghasemi, P Indra, MB Dholakia Theoretical and Applied Climatology 128 (1-2), 255-273, 2017 | 182 | 2017 |
| A comparative assessment of flood susceptibility modeling using Multi-Criteria Decision-Making Analysis and Machine Learning Methods K Khosravi, H Shahabi, BT Pham, J Adamowski, A Shirzadi, B Pradhan, ... Journal of Hydrology 573, 311-323, 2019 | 114 | 2019 |
| Spatial prediction of landslides using a hybrid machine learning approach based on random subspace and classification and regression trees BT Pham, I Prakash, DT Bui Geomorphology 303, 256-270, 2018 | 104 | 2018 |
| Landslide susceptibility modeling using Reduced Error Pruning Trees and different ensemble techniques: Hybrid machine learning approaches BT Pham, I Prakash, SK Singh, A Shirzadi, H Shahabi, DT Bui Catena 175, 203-218, 2019 | 99 | 2019 |
| A novel hybrid intelligent model of support vector machines and the MultiBoost ensemble for landslide susceptibility modeling BT Pham, A Jaafari, I Prakash, DT Bui Bulletin of Engineering Geology and the Environment 78 (4), 2865-2886, 2019 | 96 | 2019 |
| 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, DT Bui, MB Dholakia, I Prakash, HV Pham Geotechnical and Geological Engineering 34 (6), 1807-1824, 2016 | 91 | 2016 |
| 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 | 81 | 2018 |
| Rotation forest fuzzy rule-based classifier ensemble for spatial prediction of landslides using GIS BT Pham, DT Bui, I Prakash, MB Dholakia Natural Hazards 83 (1), 97-127, 2016 | 80 | 2016 |
| A novel artificial intelligence approach based on Multi-layer Perceptron Neural Network and Biogeography-based Optimization for predicting coefficient of consolidation of soil BT Pham, MD Nguyen, KTT Bui, I Prakash, K Chapi, DT Bui Catena 173, 302-311, 2019 | 65 | 2019 |
| Hybrid machine learning approaches for landslide susceptibility modeling VV Nguyen, BT Pham, BT Vu, I Prakash, S Jha, H Shahabi, A Shirzadi, ... Forests 10 (2), 157, 2019 | 62 | 2019 |
| Bagging based support vector machines for spatial prediction of landslides BT Pham, DT Bui, I Prakash Environmental earth sciences 77 (4), 146, 2018 | 61 | 2018 |
| Landslide susceptibility assessment using bagging ensemble based alternating decision trees, logistic regression and J48 decision trees methods: a comparative study BT Pham, DT Bui, I Prakash Geotechnical and Geological Engineering 35 (6), 2597-2611, 2017 | 59 | 2017 |
| A novel hybrid approach of landslide susceptibility modelling using rotation forest ensemble and different base classifiers BT Pham, I Prakash, J Dou, SK Singh, PT Trinh, HT Tran, TM Le, ... Geocarto International 35 (12), 1267-1292, 2020 | 55 | 2020 |
| A comparison study of DRASTIC methods with various objective methods for groundwater vulnerability assessment K Khosravi, M Sartaj, FTC Tsai, VP Singh, N Kazakis, AM Melesse, ... Science of the total environment 642, 1032-1049, 2018 | 55 | 2018 |
| Development of artificial intelligence models for the prediction of Compression Coefficient of soil: An application of Monte Carlo sensitivity analysis BT Pham, MD Nguyen, D Van Dao, I Prakash, HB Ly, TT Le, LS Ho, ... Science of The Total Environment 679, 172-184, 2019 | 54 | 2019 |
| A novel ensemble classifier of rotation forest and Naïve Bayer for landslide susceptibility assessment at the Luc Yen district, Yen Bai Province (Viet Nam) using GIS BT Pham, DT Bui, MB Dholakia, I Prakash, HV Pham, K Mehmood, HQ Le Geomatics, Natural Hazards and Risk 8 (2), 649-671, 2017 | 54 | 2017 |
| 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 | 53 | 2017 |
Biswajeet Pradhan (SMIEEE)Distinguished Prof. & Director, CAMGIS, UTS, Australia; Highly Cited ResearcherVerified email at uts.edu.au
