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

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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Bibliographic Details
Main Authors: Yuqian Ren, Chuanqi Huang, Yushan Jiang, Zhaoxia Wu
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Metals
Subjects:
sintering
moisture content prediction
KPCA
GA-BP hybrid prediction model
Online Access:https://www.mdpi.com/2075-4701/12/8/1287

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