| Deep-based conditional probability density function forecasting of residential loads M Afrasiabi, M Mohammadi, M Rastegar, L Stankovic, S Afrasiabi, ... IEEE Transactions on Smart Grid 11 (4), 3646-3657, 2020 | 118 | 2020 |
| Multi-agent microgrid energy management based on deep learning forecaster M Afrasiabi, M Mohammadi, M Rastegar, A Kargarian Energy 186, 115873, 2019 | 111 | 2019 |
| Integration of accelerated deep neural network into power transformer differential protection S Afrasiabi, M Afrasiabi, B Parang, M Mohammadi IEEE Transactions on Industrial Informatics 16 (2), 865-876, 2019 | 101 | 2019 |
| Advanced deep learning approach for probabilistic wind speed forecasting M Afrasiabi, M Mohammadi, M Rastegar, S Afrasiabi IEEE Transactions on Industrial Informatics 17 (1), 720-727, 2020 | 88 | 2020 |
| Designing a composite deep learning based differential protection scheme of power transformers S Afrasiabi, M Afrasiabi, B Parang, M Mohammadi Applied Soft Computing 87, 105975, 2020 | 56 | 2020 |
| Probabilistic deep neural network price forecasting based on residential load and wind speed predictions M Afrasiabi, M Mohammadi, M Rastegar, A Kargarian IET Renewable Power Generation 13 (11), 1840-1848, 2019 | 39 | 2019 |
| Real-time bearing fault diagnosis of induction motors with accelerated deep learning approach S Afrasiabi, M Afrasiabi, B Parang, M Mohammadi 2019 10th international power electronics, drive systems and technologies …, 2019 | 37 | 2019 |
| Power transformers internal fault diagnosis based on deep convolutional neural networks M Afrasiabi, S Afrasiabi, B Parang, M Mohammadi Journal of Intelligent & Fuzzy Systems 37 (1), 1165-1179, 2019 | 33 | 2019 |
| Deep learning architecture for direct probability density prediction of small‐scale solar generation M Afrasiabi, M Mohammadi, M Rastegar, S Afrasiabi IET Generation, Transmission & Distribution 14 (11), 2017-2025, 2020 | 27 | 2020 |
| Deep learning forecaster-based controller for SVC: Wind farm flicker mitigation H Samet, S Ketabipour, M Afrasiabi, S Afrasiabi, M Mohammadi IEEE Transactions on Industrial Informatics 18 (10), 7030-7037, 2020 | 25 | 2020 |
| Detection and Classification of Multiple Power Quality Disturbances based on Temporal Deep Learning M Mohammadi, M Afrasiabi, S Afrasiabi, B Parang 2019 IEEE International Conference on Environment and Electrical Engineering …, 2019 | 23 | 2019 |
| Wind turbine fault diagnosis with generative-temporal convolutional neural network S Afrasiabi, M Afrasiabi, B Parang, M Mohammadi, MM Arefi, M Rastegar 2019 IEEE International Conference on Environment and Electrical Engineering …, 2019 | 22 | 2019 |
| Fast GRNN-based method for distinguishing inrush currents in power transformers S Afrasiabi, M Afrasiabi, B Parang, M Mohammadi, H Samet, T Dragicevic IEEE Transactions on Industrial Electronics 69 (8), 8501-8512, 2021 | 21 | 2021 |
| Fault localisation and diagnosis in transmission networks based on robust deep Gabor convolutional neural network and PMU measurements S Afrasiabi, M Afrasiabi, M Mohammadi, B Parang IET Generation, Transmission & Distribution 14 (26), 6484-6492, 2020 | 21 | 2020 |
| Prediction of wind farm reactive power fast variations by adaptive one-dimensional convolutional neural network H Samet, S Ketabipour, S Afrasiabi, M Afrasiabi, M Mohammadi Computers & Electrical Engineering 96, 107480, 2021 | 18 | 2021 |
| Modulated Gabor filter based deep convolutional network for electrical motor bearing fault classification and diagnosis S Afrasiabi, M Mohammadi, M Afrasiabi, B Parang IET science, measurement & technology 15 (2), 154-162, 2021 | 18 | 2021 |
| Ensemble kalman filter based dynamic state estimation of PMSG-based wind turbine S Afrasiabi, M Afrasiabi, M Rastegar, M Mohammadi, B Parang, ... 2019 IEEE Texas Power and Energy Conference (TPEC), 1-4, 2019 | 18 | 2019 |
| Probability density function forecasting of residential electric vehicles charging profile AJ Jahromi, M Mohammadi, S Afrasiabi, M Afrasiabi, J Aghaei Applied Energy 323, 119616, 2022 | 17 | 2022 |
| Two-stage deep learning-based wind turbine condition monitoring using SCADA data S Afrasiabi, M Afrasiabi, B Parang, M Mohammadi, S Kahourzade, ... 2020 IEEE International Conference on Power Electronics, Drives and Energy …, 2020 | 15 | 2020 |
| Wide-area composite load parameter identification based on multi-residual deep neural network S Afrasiabi, M Afrasiabi, MA Jarrahi, M Mohammadi, J Aghaei, MS Javadi, ... IEEE Transactions on Neural Networks and Learning Systems 34 (9), 6121-6131, 2021 | 12 | 2021 |
mohammad mohammadishiraz universityVerified email at shirazu.ac.ir
