… The prediction algorithms covered in this paper are SVR, BPNN, RF, GBDT, and XGBoost. …
are traditional energy prediction algorithms. The other three are tree-ensemble algorithms. …

… (HVAC)– by using a model of the building to capture its dynamic … algorithm that uses a
full-complexity grey-box simulation model to optimize HVAC operation in non-residential buildings…

… The findings of this research can help residential building owners/managers make more
informed decisions around the selection of efficient heating management systems to save on …

… , both rule-based and predictive, are tested on a calibrated building simulation model of the
… of the smart algorithm for the described residential building. The algorithm is defined by four …

… of the consumed energy of heating systems in residential buildings due to various variables
… to improve the prediction of heating energy consumption in residential buildings. In this …

… The results show that both lines are almost going side by side which indicates that our
prediction algorithm is working nicely. To get better insight, we present absolute error difference …

… that of the conventional approaches, ie, GBDT and BP, this paper demonstrates the superiority
of SVMs with the sampling algorithm in the prediction of electricity consumption ratings for …

… But, there is still plenty of work in developing methods by combination of noise removal,
clustering with prediction algorithms for HL and CL prediction in order to exploit all their …

… In addition, some studies compared the performance of prediction algorithms for energy
consumption prediction in hotels. The comparison highlight the significance of ANN-based …

… In this research, the MLP neural network has been optimized using five algorithms mentioned
in the second section, and the HL and CL of a residential building have been simulated. …