December 2023
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3 Reads
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1 Citation
Transactions of the Korean Society of Mechanical Engineers B
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Publications (1)
Citations (1)
... Ji et al. [8] developed a deep neural network (DNN) model to predict hot water heating energy consumption in apartment buildings considering various independent variables; their model considering holidays as well as climatic factors achieved the best predictive performance, followed by a model considering climatic factors and one considering outdoor temperatures. Kim et al. [9] utilized Multi Linear Regression (MLR) and the Multilayer Perceptron (MLP), Support Vector Machine (SVM), and Random Forest (RF) algorithms to predict the electricity consumption of buildings, addressing temporal resolution and comparing algorithms to improve predictive accuracy. ...
- Citing Article
December 2023
Transactions of the Korean Society of Mechanical Engineers B