| Correlation and instance based feature selection for electricity load forecasting I Koprinska, M Rana, VG Agelidis Knowledge-Based Systems 82, 29-40, 2015 | 255 | 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 | 231 | 2016 |
| Forecasting electricity load with advanced wavelet neural networks M Rana, I Koprinska Neurocomputing 182, 118-132, 2016 | 183 | 2016 |
| 2D-interval forecasts for solar power production M Rana, I Koprinska, VG Agelidis Solar Energy 122, 191-203, 2015 | 107 | 2015 |
| 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 | 97 | 2020 |
| 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 | 62 | 2015 |
| SSDNet: State space decomposition neural network for time series forecasting Y Lin, I Koprinska, M Rana 2021 IEEE International conference on data mining (ICDM), 370-378, 2021 | 53 | 2021 |
| 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 | 52 | 2013 |
| Temporal convolutional attention neural networks for time series forecasting Y Lin, I Koprinska, M Rana 2021 International joint conference on neural networks (IJCNN), 1-8, 2021 | 48 | 2021 |
| 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 | 45 | 2016 |
| 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 | 43 | 2011 |
| 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 | 38 | 2020 |
| A data-driven approach based on quantile regression forest to forecast cooling load for commercial buildings M Rana, S Sethuvenkatraman, M Goldsworthy Sustainable Cities and Society 76, 103511, 2022 | 33 | 2022 |
| 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 | 30 | 2013 |
| Clustering Based Methods for Solar Power Forecasting Z Wang, I Koprinska, M Rana International Joint Conference on Neural Networks (IJCNN), 2016 | 27 | 2016 |
| Machine learning approach to investigate the influence of water quality on aquatic livestock in freshwater ponds M Rana, A Rahman, J Dabrowski, S Arnold, J McCulloch, B Pais Biosystems Engineering 208, 164-175, 2021 | 25 | 2021 |
| SpringNet: Transformer and Spring DTW for time series forecasting Y Lin, I Koprinska, M Rana Neural Information Processing: 27th International Conference, ICONIP 2020 …, 2020 | 25 | 2020 |
| 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 | 25 | 2014 |
| An integrated framework of sensing, machine learning, and augmented reality for aquaculture prawn farm management A Rahman, M Xi, JJ Dabrowski, J McCulloch, S Arnold, M Rana, A George, ... Aquacultural Engineering 95, 102192, 2021 | 23 | 2021 |
| A data-driven approach for forecasting state level aggregated solar photovoltaic power production M Rana, A Rahman, J Jin 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 19 | 2020 |
Irena KoprinskaSchool of Computer Science, University of SydneyVerifierad e-postadress på sydney.edu.au