Metalurgija | |
End point prediction of basic oxygen furnace (BOF) steelmaking based on improved bat-neural network | |
Liu, H.1  | |
[1] School of Science, University of Science and Technology Liaoning, Anshan, China | |
关键词: steelmaking; BOF; end point prediction; back propagation (BP) neural network; bat algorithm; | |
DOI : | |
学科分类:金属与冶金 | |
来源: Hrvatsko Metalursko Drustvo | |
【 摘 要 】
A mixed bat optimization algorithm based on chaos and differential evolution (CDEBA) is proposed for the endblow process of basic oxygen furnance (BOF) after sub-lance detection, and a prediction model based on BP neural network optimized by chaotic differential bat algorithm (CDEBA-NN) is presented. The simulation results show that the prediction model of carbon content achieves a hit rate of 94 % with the error range of 0,005 %, and 90 % for temperature with the error range of 15 °C, the accuracy is higher than the traditional neural network model, and then it verifies the effectiveness of the proposed model.
【 授权许可】
CC BY
【 预 览 】
Files | Size | Format | View |
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RO201910255500118ZK.pdf | 425KB | download |