Neural Network Prediction Model for Sinter Mixture Water Content Based on KPCA-GA Optimization

The design and optimization of a sinter mixture moisture controlling system usually require complex process mechanisms and time-consuming field experimental simulations. Based on BP neural networks, a new KPCA-GA optimization method is proposed to predict the mixture moisture content sequential valu...

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Detalhes bibliográficos

Principais autores:	Yuqian Ren, Chuanqi Huang, Yushan Jiang, Zhaoxia Wu
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2022-07-01
coleção:	Metals
Assuntos:	sintering moisture content prediction KPCA GA-BP hybrid prediction model
Acesso em linha:	https://www.mdpi.com/2075-4701/12/8/1287
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