Md Mashud Rana

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Irena KoprinskaSchool of Computer Science, University of SydneyVerified email at sydney.edu.au
Vassilios G Agelidis, FIEEE, FIETProfessor, Technical University of Denmark, Lyngby, Copenhagen, DenmarkVerified email at elektro.dtu.dk
Ashfaqur RahmanTeam Leader and Principal Research Scientist, Data61, CSIRO, Senior Member, IEEEVerified email at csiro.au
Alicia Troncoso (ORCID: 0000-0002-9...Full Professor, Data Science & Big Data Lab, Universidad Pablo de OlavideVerified email at upo.es
John McCullochResearch Engineer, Data61 CSIROVerified email at csiro.au
Subbu SethuvenkatramanCSIROVerified email at csiro.au
Joel Janek DabrowskiCSIROVerified email at data61.csiro.au
Khandakar AhmedSenior Lecturer, Victoria UniversityVerified email at ieee.org
Francisco Martínez-ÁlvarezFull Professor, Data Science & Big Data Lab, Pablo de Olavide University of Seville, SpainVerified email at upo.es
Margaret HamiltonProfessor, School of Computing Technologies, RMIT UniversityVerified email at rmit.edu.au
Mohammad Saiedur RahamanLecturer, Central Queensland University, AustraliaVerified email at cqu.edu.au
Sarah AlmaghrabiCS PhD candidate at RMIT University | Academic at the University of Jeddah | Information TechnologyVerified email at student.rmit.edu.au
Daniel SmithCommonwealth Science and Industrial Research Organisation (CSIRO)Verified email at csiro.au
Andrew HellicarCSIRO Computational InformaticsVerified email at csiro.au
Jiong JinAssociate Professor, Swinburne University of Technology, Melbourne, AustraliaVerified email at swin.edu.au
Baumgartner Peter O.professeur de Géologie, Université de LausanneVerified email at unil.ch
Rohitash ChandraUNSWVerified email at unsw.edu.au
Abbas KhosraviAssociate ProfessorVerified email at deakin.edu.au

Md Mashud Rana

Data61 | CSIRO

Verified email at data61.csiro.au

data science machine learning deep learning time series


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Correlation and instance based feature selection for electricity load forecasting I Koprinska, M Rana, VG Agelidis Knowledge-Based Systems 82, 29-40, 2015	236	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	196	2016
Forecasting electricity load with advanced wavelet neural networks M Rana, I Koprinska Neurocomputing 182, 118-132, 2016	164	2016
2D-interval forecasts for solar power production M Rana, I Koprinska, VG Agelidis Solar Energy 122, 191-203, 2015	99	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	70	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	59	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	49	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	39	2011
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	35	2016
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	28	2013
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	24	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	24	2014
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	22	2021
Clustering Based Methods for Solar Power Forecasting Z Wang, I Koprinska, M Rana International Joint Conference on Neural Networks (IJCNN), 2016	22	2016
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	19	2022
SpringNet: Transformer and Spring DTW for time series forecasting Y Lin, I Koprinska, M Rana Neural Information Processing: 27th International Conference, ICONIP 2020 …, 2020	19	2020
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	18	2021
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	15	2021
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	15	2017
Solar power forecasting using pattern sequences Z Wang, I Koprinska, M Rana Artificial Neural Networks and Machine Learning–ICANN 2017: 26th …, 2017	15	2017

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