| Correlation and instance based feature selection for electricity load forecasting I Koprinska, M Rana, VG Agelidis Knowledge-Based Systems 82, 29-40, 2015 | 189 | 2015 |
| Univariate and multivariate methods for very short-term solar photovoltaic power forecasting M Rana, I Koprinska, VG Agelidis Energy Conversion and Management 121, 380–390, 2016 | 155 | 2016 |
| Forecasting electricity load with advanced wavelet neural networks M Rana, I Koprinska Neurocomputing 182, 118-132, 2016 | 143 | 2016 |
| 2D-interval forecasts for solar power production M Rana, I Koprinska, VG Agelidis Solar Energy 122, 191-203, 2015 | 84 | 2015 |
| Forecasting solar power generated by grid connected PV systems using ensembles of neural networks M Rana, I Koprinska, VG Agelidis 2015 International Joint Conference on Neural Networks (IJCNN), 1-8, 2015 | 50 | 2015 |
| Combining pattern sequence similarity with neural networks for forecasting electricity demand time series I Koprinska, M Rana, A Troncoso, F Martínez-Álvarez The 2013 International Joint Conference on Neural Networks (IJCNN), 1-8, 2013 | 45 | 2013 |
| Yearly and seasonal models for electricity load forecasting I Koprinska, M Rana, VG Agelidis The 2011 International Joint Conference on Neural Networks, 1474-1481, 2011 | 40 | 2011 |
| Multiple steps ahead solar photovoltaic power forecasting based on univariate machine learning models and data re-sampling M Rana, A Rahman Sustainable Energy, Grids and Networks 21, 100286, 2020 | 37 | 2020 |
| Prediction intervals for electricity load forecasting using neural networks M Rana, I Koprinska, A Khosravi, VG Agelidis The 2013 international joint conference on neural networks (IJCNN), 1-8, 2013 | 25 | 2013 |
| Solar power forecasting using weather type clustering and ensembles of neural networks M Rana, I Koprinska, VG Agelidis 2016 International Joint Conference on Neural Networks (IJCNN), 4962-4969, 2016 | 23 | 2016 |
| Forecasting hourly electricity load profile using neural networks M Rana, I Koprinska, A Troncoso 2014 International joint conference on neural networks (IJCNN), 824-831, 2014 | 23 | 2014 |
| Temporal convolutional neural networks for solar power forecasting Y Lin, I Koprinska, M Rana 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 14 | 2020 |
| Neural network ensemble based approach for 2D-interval prediction of solar photovoltaic power M Rana, I Koprinska Energies 9 (10), 829, 2016 | 14 | 2016 |
| Clustering Based Methods for Solar Power Forecasting Z Wang, I Koprinska, M Rana International Joint Conference on Neural Networks (IJCNN), 2016 | 14 | 2016 |
| Solar power forecasting using pattern sequences Z Wang, I Koprinska, M Rana International Conference on Artificial Neural Networks, 486-494, 2017 | 12 | 2017 |
| Feature selection for interval forecasting of electricity demand time series data M Rana, I Koprinska, A Khosravi Artificial Neural Networks, 445-462, 2015 | 12 | 2015 |
| Feature selection for electricity load prediction M Rana, I Koprinska, VG Agelidis International Conference on Neural Information Processing, 526-534, 2012 | 12 | 2012 |
| Solar power prediction using weather type pair patterns Z Wang, I Koprinska, M Rana 2017 International Joint Conference on Neural Networks (IJCNN), 4259-4266, 2017 | 11 | 2017 |
| Electricity load forecasting: a weekday-based approach I Koprinska, M Rana, VG Agelidis International Conference on Artificial Neural Networks, 33-41, 2012 | 9 | 2012 |
| SpringNet: Transformer and Spring DTW for time series forecasting Y Lin, I Koprinska, M Rana International Conference on Neural Information Processing, 616-628, 2020 | 8 | 2020 |
Irena KoprinskaSchool of Computer Science, University of SydneyVerified email at it.usyd.edu.au
