Operational Demand Forecasting In District Heating Systems Using Ensembles Of Online Machine Learning Algorithms
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Davy Geysen | Niklas Lavesson | Dirk Vanhoudt | Oscar De Somer | Christian Johansson | Markus Bergkvist | N. Lavesson | D. Vanhoudt | C. Johansson | M. Bergkvist | D. Geysen
[1] H. Madsen,et al. Short-term heat load forecasting for single family houses , 2013 .
[2] Yeong-Koo Yeo,et al. Heat consumption forecasting using partial least squares, artificial neural network and support vector regression techniques in district heating systems , 2010 .
[3] Sven Werner. District Heating and Cooling , 2013 .
[4] Masatoshi Sakawa,et al. HEAT LOAD PREDICTION IN DISTRICT HEATING AND COOLING SYSTEMS THROUGH A RECURRENT NEURAL NETWORK WITH DATA CHARACTERISTICS , 2010 .
[5] Saso Dzeroski,et al. Learning model trees from evolving data streams , 2010, Data Mining and Knowledge Discovery.
[6] Spyridon Provatas,et al. An Online Machine Learning Algorithm for Heat Load Forecasting in District Heating Systems , 2014 .
[7] Erik Dotzauer,et al. Simple model for prediction of loads in district-heating systems , 2002 .
[8] H. Madsen,et al. Modelling the heat consumption in district heating systems using a grey-box approach , 2006 .
[9] Albert Bifet,et al. DATA STREAM MINING A Practical Approach , 2009 .
[10] Masatoshi Sakawa,et al. Heat load prediction through recurrent neural network in district heating and cooling systems , 2008, 2008 IEEE International Conference on Systems, Man and Cybernetics.