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@inproceedings{1204453, author = {Jurčo, Juraj and Popelínský, Lubomír and Křehlík, Karel}, address = {Praha}, booktitle = {Znalosti 2014}, edition = {1. vydání}, editor = {Vojtěch Svátek, Ondřej Zamazal}, keywords = {meta-learning; model prediction; boiler; NOx}, howpublished = {elektronická verze "online"}, language = {eng}, location = {Praha}, isbn = {978-80-245-2054-4}, pages = {98-103}, publisher = {Vysoká škola ekonomická v Praze}, title = {Emission prediction of a thermal power plant}, year = {2014} }
TY - JOUR ID - 1204453 AU - Jurčo, Juraj - Popelínský, Lubomír - Křehlík, Karel PY - 2014 TI - Emission prediction of a thermal power plant PB - Vysoká škola ekonomická v Praze CY - Praha SN - 9788024520544 KW - meta-learning KW - model prediction KW - boiler KW - NOx N2 - The task of prediction of emissions is very challenging and also important. We argued that simple learning techniques that learn only one predictive model are not powerful enough in more complex situations. Better predictive results can be achieved by splitting data into smaller parts and for each part to learn a sub-model. We proposed and tested a novel method that combines meta-learning and ensemble learning. We showed that there is significant increase in prediction accuracy. ER -
JURČO, Juraj, Lubomír POPELÍNSKÝ a Karel KŘEHLÍK. Emission prediction of a thermal power plant. Online. In Vojtěch Svátek, Ondřej Zamazal. \textit{Znalosti 2014}. 1. vydání. Praha: Vysoká škola ekonomická v Praze, 2014, s.~98-103. ISBN~978-80-245-2054-4.
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