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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-07-01
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| Series: | Metals |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4701/12/8/1287 |