| Prediction success of machine learning methods for flash flood susceptibility mapping in the Tafresh watershed, Iran S Janizadeh, M Avand, A Jaafari, TV Phong, M Bayat, E Ahmadisharaf, ... Sustainability 11 (19), 5426, 2019 | 257 | 2019 |
| Flash flood susceptibility modeling using new approaches of hybrid and ensemble tree-based machine learning algorithms SS Band, S Janizadeh, S Chandra Pal, A Saha, R Chakrabortty, ... Remote Sensing 12 (21), 3568, 2020 | 190 | 2020 |
| GIS based hybrid computational approaches for flash flood susceptibility assessment BT Pham, M Avand, S Janizadeh, TV Phong, N Al-Ansari, LS Ho, S Das, ... Water 12 (3), 683, 2020 | 184 | 2020 |
| Improvement of best first decision trees using bagging and dagging ensembles for flood probability mapping P Yariyan, S Janizadeh, T Van Phong, HD Nguyen, R Costache, ... Water Resources Management 34, 3037-3053, 2020 | 152 | 2020 |
| Novel ensemble approach of deep learning neural network (DLNN) model and particle swarm optimization (PSO) algorithm for prediction of gully erosion susceptibility SS Band, S Janizadeh, S Chandra Pal, A Saha, R Chakrabortty, M Shokri, ... Sensors 20 (19), 5609, 2020 | 142 | 2020 |
| Flood susceptibility mapping using an improved analytic network process with statistical models P Yariyan, M Avand, RA Abbaspour, A Torabi Haghighi, R Costache, ... Geomatics, Natural Hazards and Risk 11 (1), 2282-2314, 2020 | 133 | 2020 |
| GIS-based machine learning algorithms for gully erosion susceptibility mapping in a semi-arid region of Iran X Lei, W Chen, M Avand, S Janizadeh, N Kariminejad, H Shahabi, ... Remote Sensing 12 (15), 2478, 2020 | 131 | 2020 |
| Evaluation of different boosting ensemble machine learning models and novel deep learning and boosting framework for head-cut gully erosion susceptibility W Chen, X Lei, R Chakrabortty, SC Pal, M Sahana, S Janizadeh Journal of Environmental Management 284, 112015, 2021 | 128 | 2021 |
| Forest fire susceptibility prediction based on machine learning models with resampling algorithms on remote sensing data B Kalantar, N Ueda, MO Idrees, S Janizadeh, K Ahmadi, F Shabani Remote Sensing 12 (22), 3682, 2020 | 123 | 2020 |
| Mapping the spatial and temporal variability of flood hazard affected by climate and land-use changes in the future S Janizadeh, SC Pal, A Saha, I Chowdhuri, K Ahmadi, S Mirzaei, ... Journal of Environmental Management 298, 113551, 2021 | 121 | 2021 |
| Evaluation efficiency of hybrid deep learning algorithms with neural network decision tree and boosting methods for predicting groundwater potential Y Chen, W Chen, S Chandra Pal, A Saha, I Chowdhuri, B Adeli, ... Geocarto International 37 (19), 5564-5584, 2022 | 114 | 2022 |
| Ensemble models of GLM, FDA, MARS, and RF for flood and erosion susceptibility mapping: a priority assessment of sub-basins A Mosavi, M Golshan, S Janizadeh, B Choubin, AM Melesse, AA Dineva Geocarto International 37 (9), 2541-2560, 2022 | 114 | 2022 |
| A tree-based intelligence ensemble approach for spatial prediction of potential groundwater PTTNVHN Mohammadtaghi Avanda , Saeid Janizadeha , Dieu Tien Buib,c, Viet Hoa ... INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2020 | 114 | 2020 |
| A comparative assessment of random forest and k-nearest neighbor classifiers for gully erosion susceptibility mapping M Avand, S Janizadeh, SA Naghibi, HR Pourghasemi, ... Water 11 (10), 2076, 2019 | 110 | 2019 |
| GIS-based gully erosion susceptibility mapping: a comparison of computational ensemble data mining models VH Nhu, S Janizadeh, M Avand, W Chen, M Farzin, E Omidvar, A Shirzadi, ... Applied Sciences 10 (6), 2039, 2020 | 98 | 2020 |
| Modelling multi-hazard threats to cultural heritage sites and environmental sustainability: The present and future scenarios A Saha, SC Pal, M Santosh, S Janizadeh, I Chowdhuri, A Norouzi, P Roy, ... Journal of Cleaner Production 320, 128713, 2021 | 92 | 2021 |
| Comparative analysis of artificial intelligence models for accurate estimation of groundwater nitrate concentration SS Band, S Janizadeh, SC Pal, I Chowdhuri, Z Siabi, A Norouzi, ... Sensors 20 (20), 5763, 2020 | 74 | 2020 |
| Deep neural network utilizing remote sensing datasets for flood hazard susceptibility mapping in Brisbane, Australia B Kalantar, N Ueda, V Saeidi, S Janizadeh, F Shabani, K Ahmadi, ... Remote Sensing 13 (13), 2638, 2021 | 71 | 2021 |
| Comparison of machine learning methods for mapping the stand characteristics of temperate forests using multi-spectral sentinel-2 data K Ahmadi, B Kalantar, V Saeidi, EKG Harandi, S Janizadeh, N Ueda Remote Sensing 12 (18), 3019, 2020 | 67 | 2020 |
| Deep learning and boosting framework for piping erosion susceptibility modeling: spatial evaluation of agricultural areas in the semi-arid region Y Chen, W Chen, S Janizadeh, GS Bhunia, A Bera, QB Pham, NTT Linh, ... Geocarto International 37 (16), 4628-4654, 2022 | 57 | 2022 |