A Novel Approach for Predicting CO₂ Emissions in the Building Industry Using a Hybrid Multi-Strategy Improved Particle Swarm Optimization–Long Short-Term Memory Model

The accurate prediction of carbon dioxide (CO₂) emissions in the building industry can provide data support and theoretical insights for sustainable development. This study proposes a hybrid model for predicting CO₂ emissions that combines a multi-strategy improved particle swa...

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主要な著者:	Yuyi Hu, Bojun Wang, Yanping Yang, Liwei Yang
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2024-09-01
シリーズ:	Energies
主題:	carbon dioxide emission prediction multi-strategy improved particle swarm algorithm long short-term memory model MSPSO-LSTM model building industry
オンライン･アクセス:	https://www.mdpi.com/1996-1073/17/17/4379
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