Maneesha Perera
Maneesha Perera
Research Fellow, University of Melbourne
Verified email at - Homepage
Cited by
Cited by
Multi-resolution, multi-horizon distributed solar PV power forecasting with forecast combinations
M Perera, J De Hoog, K Bandara, S Halgamuge
Expert Systems with Applications 205, 117690, 2022
Characteristic profile: improved solar power forecasting using seasonality models
J De Hoog, M Perera, P Ilfrich, S Halgamuge
ACM SIGENERGY Energy Informatics Review 1 (1), 95-106, 2021
Day-ahead regional solar power forecasting with hierarchical temporal convolutional neural networks using historical power generation and weather data
M Perera, J De Hoog, K Bandara, D Senanayake, S Halgamuge
Applied Energy 361, 2024
Solar PV Maps for Estimation and Forecasting of Distributed Solar Generation
J de Hoog, M Perera, K Bandara, D Senanayake, S Halgamuge
ICML 2021 Workshop - Tackling Climate Change with Machine Learning, 2021
FEEDBACK trial-A randomised control trial to investigate the effect of personalised feedback and financial incentives on reducing the incidence of road crashes
M Stevenson, D Mortimer, L Meuleners, A Harris, T Senserrick, ...
BMC public health 23 (1), 2035, 2023
Accurate Forecasting of Distributed Solar Generation using Time Series and Deep Learning Methods
MGS Perera
University of Melbourne, 2022
Forecast Combinations for Multi-Horizon Residential Solar Photovoltaic Power Forecasting
M Perera, J de Hoog, K Bandara, S Halgamuge
40th International Symposium on Forecasting (ISF 2020), 2020
Hybrid Edge-Cloud based Ensemble Learning for Forecasting Occupancy of Open-plan Offices
F Jalali, S Roy, RR Kolluri, M Perera, M Salehi, J D.Vasquez, J de Hoog
ACM SIGKDD Workshop on Artificial Intelligence of Things, 2020
Using Bezier Curves to Refine Road Vector Data through Satellite Images
M Perera, D Karunaratne, E Hettiarachchi
Proceedings of the 2018 the 2nd International Conference on Video and Image …, 2018
Refinement of Existing Road Vector Layers Through High Resolution Satellite Images
MGS Perera
Forecasting Hierarchical Time Series Using Non-Linear Mappings
S Wickramasuriya, K Bandara, H Hewamalage, M Perera
Available at SSRN 4793559, 0
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