|About this Abstract
||2021 TMS Annual Meeting & Exhibition
||Materials Processing Fundamentals
||A hybrid model for predicting the end-point phosphorus
content of electric arc furnace
||Chao Chen, Nan Wang
|On-Site Speaker (Planned)
The end-point phosphorus content is one of the main target in the electric converter process.In order to stabilize the end-point phosphorus content within a narrow range, a prediction model based on the hybrid method combined with the deep layer neural network and k-means method has been employed.With this method, the accuracy of end-point phosphorus content is 93.6% within the ±0.005%. The hybrid model has achieved the effective prediction for end-point phosphorus content, and provided a good reference for end-point control in the real electric converter process.