XGBoost energy consumption prediction based on multi-system data HVAC
- URL: http://arxiv.org/abs/2105.09945v1
- Date: Thu, 20 May 2021 18:41:17 GMT
- Title: XGBoost energy consumption prediction based on multi-system data HVAC
- Authors: Yunlong Li, Yiming Peng, Dengzheng Zhang, Yingan Mai, Zhengrong Ruan
- Abstract summary: This paper extracts features from large data sets using XGBoost, trains them separately to obtain multiple models, then fuses them with LightGBM's independent prediction results using MAE.
It successfully applies this model to the self-developed Internet of Things platform.
- Score: 0.2519906683279153
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The energy consumption of the HVAC system accounts for a significant portion
of the energy consumption of the public building system, and using an efficient
energy consumption prediction model can assist it in carrying out effective
energy-saving transformation. Unlike the traditional energy consumption
prediction model, this paper extracts features from large data sets using
XGBoost, trains them separately to obtain multiple models, then fuses them with
LightGBM's independent prediction results using MAE, infers energy consumption
related variables, and successfully applies this model to the self-developed
Internet of Things platform.
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