Robust Dynamic Modeling of Bed Temperature in Utility Circulating Fluidized Bed Boilers Using a Hybrid CEEMDAN-NMI–iTransformer Framework

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Publié dans:	Processes vol. 13, no. 3 (2025), p. 816
Auteur principal:	Li, Qianyu
Autres auteurs:	Wang, Guanglong, Li, Xian, Yu, Cong, Bao, Qing, Lai, Wei, Li, Wei, Ma, Huan, Si, Fengqi
Publié:	MDPI AG
Sujets:	Outliers (statistics) Pollutants Accuracy Deep learning Fluid dynamics Long short-term memory Power plants Dynamic models Fluidized bed boilers Combustion stability Industrial plant emissions Robustness Boilers Efficiency Adaptive algorithms Heat transfer Machine learning Fluidized beds Predictions Carbon Temperature Neural networks Variables Distributed control systems Correlation analysis Algorithms Flue gas Coal Energy levels
Accès en ligne:	Citation/Abstract Full Text + Graphics Full Text - PDF
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