| CNN-LSTM vs. LSTM-CNN to predict power flow direction: a case study of the high-voltage subnet of northeast Germany F Aksan, Y Li, V Suresh, P Janik Sensors 23 (2), 901, 2023 | 55 | 2023 |
| Clustering methods for power quality measurements in virtual power plant F Aksan, M Jasiński, T Sikorski, D Kaczorowska, J Rezmer, V Suresh, ... Energies 14 (18), 5902, 2021 | 25 | 2021 |
| Probabilistic LSTM-Autoencoder based hour-ahead solar power forecasting model for intra-day electricity market participation: A Polish case study V Suresh, F Aksan, P Janik, T Sikorski, BS Revathi IEEE Access 10, 110628-110638, 2022 | 20 | 2022 |
| Load Forecasting for the Laser Metal Processing Industry Using VMD and Hybrid Deep Learning Models F Aksan, V Suresh, P Janik, T Sikorski Energies 16 (14), 5381, 2023 | 11 | 2023 |
| Multistep Forecasting of Power Flow Based on LSTM Autoencoder: A Study Case in Regional Grid Cluster Proposal F Aksan, Y Li, V Suresh, P Janik Energies 16 (13), 5014, 2023 | 5 | 2023 |
| Review of the application of deep learning for fault detection in wind turbine F Aksan, P Janik, V Suresh, Z Leonowicz 2022 IEEE International Conference on Environment and Electrical Engineering …, 2022 | 3 | 2022 |
| Multivariate Multi-step Forecasting for Cable Pooling Applications F Aksan, P Janik, V Suresh 2023 International Conference on Clean Electrical Power (ICCEP), 237-244, 2023 | 2 | 2023 |
| Optimal Capacity and Charging Scheduling of Battery Storage through Forecasting of Photovoltaic Power Production and Electric Vehicle Charging Demand with Deep Learning Models F Aksan, V Suresh, P Janik Energies 17 (11), 2718, 2024 | 1 | 2024 |
| Prediction of regional PV power generation based on LSTM-CNN F Aksan, P Janik, K Pfeiffer, V Suresh, Z Leonowicz 2023 Asia Meeting on Environment and Electrical Engineering (EEE-AM), 01-06, 2023 | | 2023 |
| Jasi nski F Aksan Romania 25, 1-4, 2020 | | 2020 |
