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Rakshitha Godahewa
Rakshitha Godahewa
Postdoctoral Research Fellow at Monash University, Australia
Verified email at monash.edu
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Cited by
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Monash time series forecasting archive
R Godahewa, C Bergmeir, GI Webb, RJ Hyndman, P Montero-Manso
35th Conference on Neural Information Processing Systems Datasets and …, 2021
922021
Ensembles of localised models for time series forecasting
R Godahewa, K Bandara, GI Webb, S Smyl, C Bergmeir
Knowledge-Based Systems 233, 107518, 2021
282021
Commentary on the M5 forecasting competition
S Kolassa
International Journal of Forecasting 38 (4), 1562-1568, 2022
20*2022
Association Between Urine Output and Mortality in Critically Ill Patients
AJ Heffernan, S Judge, SM Petrie, R Godahewa, C Bergmeir, D Pilcher, ...
Critical Care Medicine, 2021
12*2021
Simulation and optimisation of air conditioning systems using machine learning
R Godahewa, C Deng, A Prouzeau, C Bergmeir
arXiv preprint arXiv:2006.15296, 2020
92020
A strong baseline for weekly time series forecasting
R Godahewa, C Bergmeir, GI Webb, P Montero-Manso
arXiv e-prints, arXiv: 2010.08158, 2020
82020
Ieee-cis technical challenge on predict+ optimize for renewable energy scheduling
C Bergmeir, F de Nijs, S Ferraro, L Magdalena, P Stuckey, Q Bui, ...
URL: https://dx. doi. org/10.21227/1x9c-0161, doi 10, 2021
72021
A generative deep learning framework across time series to optimize the energy consumption of air conditioning systems
R Godahewa, C Deng, A Prouzeau, C Bergmeir
IEEE Access 10, 6842-6855, 2022
62022
An accurate and fully-automated ensemble model for weekly time series forecasting
R Godahewa, C Bergmeir, GI Webb, P Montero-Manso
International Journal of Forecasting 39 (2), 641-658, 2023
52023
Comparison and evaluation of methods for a predict+ optimize problem in renewable energy
C Bergmeir, F de Nijs, A Sriramulu, M Abolghasemi, R Bean, J Betts, ...
arXiv preprint arXiv:2212.10723, 2022
52022
Handling concept drift in global time series forecasting
Z Liu, R Godahewa, K Bandara, C Bergmeir
Forecasting with Artificial Intelligence: Theory and Applications, 163-189, 2023
42023
Seasonal averaged one-dependence estimators: a novel algorithm to address seasonal concept drift in high-dimensional stream classification
R Godahewa, T Yann, C Bergmeir, F Petitjean
2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020
32020
Forecasting with Artificial Intelligence: Theory and Applications
M Hamoudia, S Makridakis, E Spiliotis
Springer Nature, 2023
12023
SETAR-Tree: A Novel and Accurate Tree Algorithm for Global Time Series Forecasting
R Godahewa, GI Webb, D Schmidt, C Bergmeir
Machine Learning, 2022
12022
The Energy Prediction Smart-Meter Dataset: Analysis of Previous Competitions and Beyond
D Pekaslan, JM Alonso-Moral, K Bandara, C Bergmeir, ...
arXiv preprint arXiv:2311.04007, 2023
2023
Scalable Probabilistic Forecasting in Retail with Gradient Boosted Trees: A Practitioner's Approach
X Long, Q Bui, G Oktavian, DF Schmidt, C Bergmeir, R Godahewa, ...
arXiv preprint arXiv:2311.00993, 2023
2023
On Forecast Stability
R Godahewa, C Bergmeir, ZE Baz, C Zhu, Z Song, S García, D Benavides
arXiv preprint arXiv:2310.17332, 2023
2023
Simulation and Optimisation of Air Conditioning Systems
R Godahewa, C Deng, A Prouzeau, C Bergmeir
Monash Energy Conference, 2019
2019
Short-Term Traffic Prediction Using Visitor Location Registry Data
S Ossen, K Fernando, R Godahewa, F Dilhasha, AS Perera, M Walpola
Netmob Conference, 2017
2017
Short-term traffic prediction with visitor location registry data
F Dilhasha, K Fernando, R Godahewa, S Ossen, AS Perara, M Walpola
Engineering Research Unit, Faculty of Engiennring, University of Moratuwa, 2016
2016
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Articles 1–20