A novel time-span input neural network for accurate municipal solid waste incineration boiler steam temperature prediction

A novel time-span input neural network was developed to accurately predict the trend of the main steam temperature of a 750-t/d waste incineration boiler. Its historical operating data were used to retrieve sensitive parameters for the boiler output steam temperature by correlation analysis. Then, t...

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Veröffentlicht in:	Journal of Zhejiang University. A. Science 2021-10, Vol.22 (10), p.777-791
Hauptverfasser:	Hu, Qin-xuan, Long, Ji-sheng, Wang, Shou-kang, He, Jun-jie, Bai, Li, Du, Hai-liang, Huang, Qun-xing
Format:	Artikel
Sprache:	eng
Schlagworte:	Boilers Civil Engineering Classical and Continuum Physics Combustion Correlation analysis Engineering High temperature Incineration Industrial Chemistry/Chemical Engineering Mechanical Engineering Municipal solid waste Municipal waste management Neural networks Parameter sensitivity Performance prediction Predictions Solid waste management Steam Waste disposal
Online-Zugang:	Volltext
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