Diesel selective catalytic reduction emission prediction based on physical model data-driven and variational autoencoder-fully connected neural network-improved Bayesian algorithm (VAE-FCNN-IBO)

In order to accurately predict NOx and NH3 concentrations downstream of the diesel engine selective catalytic reduction (SCR) system and to improve computational efficiency, this paper constructs a diesel engine SCR model and combines a data-driven approach with the design of a fully connected neura...

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Veröffentlicht in:	Energy (Oxford) Jg. 337; S. 138611
Hauptverfasser:	Wenlong liu, Gao, Ying, Zhu, Qi, You, Yuelin, Xia, Bocong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 15.11.2025
Schlagworte:	Diesel engine Fully connected neural network Improved Bayesian algorithm Selective catalytic reduction Variational autoencoder Variational autoencoder Diesel engine Improved Bayesian algorithm Fully connected neural network Selective catalytic reduction
ISSN:	0360-5442
Online-Zugang:	Volltext
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