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

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Detalles Bibliográficos
Publicado en:	Processes vol. 13, no. 3 (2025), p. 816
Autor principal:	Li, Qianyu
Otros Autores:	Wang, Guanglong, Li, Xian, Yu, Cong, Bao, Qing, Lai, Wei, Li, Wei, Ma, Huan, Si, Fengqi
Publicado:	MDPI AG
Materias:	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
Acceso en línea:	Citation/Abstract Full Text + Graphics Full Text - PDF
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