A novel energy demand prediction strategy for residential buildings based on ensemble learning

Yao Huang(Huazhong University of Science and Technology), Tanveer Ahmad(Guangxi University), Yue Yuan(Hainan Meteorology Administration), Huanxin Chen(Huazhong University of Science and Technology), Jiangyu Wang(Huazhong University of Science and Technology), Yabin Guo(Zhengzhou University)
Energy Procedia
February 1, 2019
10.1016/j.egypro.2019.01.935
Cited by 58

Related Papers

A comprehensive overview on the data driven and large scale based approaches for forecasting of building energy demand: A review
|Energy and Buildings|2018|351
Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2024
|Nucleic Acids Research|2023|337
Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2025
|Nucleic Acids Research|2024|315
Machine learning-based thermal response time ahead energy demand prediction for building heating systems
|Applied Energy|2018|205
Deep learning-based fault diagnosis of variable refrigerant flow air-conditioning system for building energy saving
|Applied Energy|2018|169