A hybrid method of cooling load forecasting for large commercial building based on extreme learning machine

Air conditioning system is extensively used in large commercial buildings. The fast and accurate building cooling load forecasting is the basis for improving the operation efficiency of the air conditioning system, which is conducive to implement the effective management of the air conditioning syst...

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Vydáno v:	Energy (Oxford) Ročník 238; s. 122073
Hlavní autoři:	Gao, Zhikun, Yu, Junqi, Zhao, Anjun, Hu, Qun, Yang, Siyuan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Oxford Elsevier Ltd 01.01.2022 Elsevier BV
Témata:	air Air conditioning Algorithms Artificial neural networks Buildings China Commercial buildings Cooling Cooling loads Cooling systems energy Energy conservation Energy management Extreme learning machine Forecasting Hybrid systems Large commercial building cooling load Learning algorithms Machine learning Mathematical models Neural networks Optimization Parameters prediction Prediction accuracy Prediction models Random forest Root-mean-square errors Whale optimization algorithm whales China Prediction accuracy Random forest Whale optimization algorithm Large commercial building cooling load Extreme learning machine
ISSN:	0360-5442, 1873-6785
On-line přístup:	Získat plný text
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