Flood Prediction Using Machine Learning Models: Literature Review A Mosavi | 1167 | 2018 |
An ensemble prediction of flood susceptibility using multivariate discriminant analysis, classification and regression trees, and support vector machines B Choubin, E Moradi, M Golshan, J Adamowski, A Mosavi Elsevier Journal Science of the Total Environment 651, 2087-2096, 2019 | 614 | 2019 |
Covid-19 outbreak prediction with machine learning SF Ardabili, A Mosavi, P Ghamisi, F Ferdinand, AR Varkonyi-Koczy, ... | 526 | 2020 |
Sustainable Business Models: A Review S Nosratabadi, A Mosavi, E Kazimieras Zavadskas, A Rakotonirainy, ... | 513 | 2019 |
State of the art of machine learning models in energy systems, a systematic review A Mosavi, M Salimi, S Faizollahzadeh Ardabili, T Rabczuk, ... | 455 | 2019 |
COVID-19 pandemic prediction for Hungary; a hybrid machine learning approach G Pinter, I Felde, A Mosavi, P Ghamisi, R Gloaguen | 357 | 2020 |
Predicting stock market trends using machine learning and deep learning algorithms via continuous and binary data; a comparative analysis M Nabipour, P Nayyeri, H Jabani, A Mosavi Ieee Access 8, 150199-150212, 2020 | 326 | 2020 |
Deep learning for stock market prediction M Nabipour, P Nayyeri, H Jabani, A Mosavi, E Salwana | 321 | 2020 |
Predicting standardized streamflow index for hydrological drought using machine learning models S Band, S Hashemi, H Salimi, S Samadianfard, E Asadi, S Shadkani, ... Engineering Applications of Computational Fluid Mechanics 14 (1), 339-350, 2020 | 282 | 2020 |
Flash-flood hazard assessment using ensembles and Bayesian-based machine learning models: application of the simulated annealing feature selection method FS Hosseini, B Choubin, A Mosavi, N Nabipour, S Band, H Darabi, ... Science of the total environment 711, 135161, 2020 | 277 | 2020 |
List of Deep Learning Models A Mosavi, SF Ardabili, AR Várkonyi-Kóczy International Conference on Global Research and Education, 2019 | 256* | 2019 |
Ensemble models with uncertainty analysis for multi-day ahead forecasting of chlorophyll a concentration in coastal waters S Band, E Jafari Nodoushan, JE Adolf, A Abdul Manaf, A Mosavi, K Chau Engineering Applications of Computational Fluid Mechanics 13 (1), 91-101, 2019 | 246 | 2019 |
Deep learning for detecting building defects using convolutional neural networks H Perez, JHM Tah, A Mosavi Sensors 19 (16), 3556, 2019 | 236 | 2019 |
Advances in machine learning modeling reviewing hybrid and ensemble methods S Ardabili, A Mosavi, AR Várkonyi-Kóczy International conference on global research and education, 215-227, 2019 | 214 | 2019 |
Integrated machine learning methods with resampling algorithms for flood susceptibility prediction E Dodangeh, B Choubin, AN Eigdir, N Nabipour, M Panahi, ... Science of the Total Environment 705, 135983, 2020 | 206 | 2020 |
Meta-heuristic algorithm-tuned neural network for breast cancer diagnosis using ultrasound images S Bourouis, A Mosavi, S Agrawal, M Hamdi | 202 | 2021 |
Prediction of hydropower generation using grey wolf optimization adaptive neuro-fuzzy inference system M Dehghani, H Riahi-Madvar, F Hooshyaripor, A Mosavi, ... | 199 | 2019 |
Comprehensive review of deep reinforcement learning methods and applications in economics A Mosavi, Y Faghan, P Ghamisi, P Duan, SF Ardabili, E Salwana, ... | 195 | 2020 |
Predicting and mapping of soil organic carbon using machine learning algorithms in Northern Iran M Emadi, R Taghizadeh-Mehrjardi, A Cherati, M Danesh, A Mosavi, ... Remote Sensing 12 (14), 2234, 2020 | 188 | 2020 |
Ensemble boosting and bagging based machine learning models for groundwater potential prediction A Mosavi, F Sajedi Hosseini, B Choubin, M Goodarzi, AA Dineva, ... Water Resources Management 35, 23-37, 2021 | 185 | 2021 |