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A neural network prediction analysis of breakout continuous casting based on differential evolution (DE)

Y. R. Li ; Institute of Applied Technology, University of Science and Technology Liaoning, China
C. N. Zhang ; School of Software, University of Science and Technology Liaoning, China

Puni tekst: engleski pdf 553 Kb

str. 291-294

preuzimanja: 462



In order to predict the breakout of continuous casting accurately and timely, a breakout prediction neural network (BPNN) model based on differential evolution algorithm was proposed. Differential evolutionary algorithm is introduced to solve the problem of fast optimization. The pretreatment of weights and thresholds improves the accuracy of breakout. The experimental analysis shows that the convergence speed of DE-BPNN breakout prediction model is faster than that of traditional neural network, and the recognition ability are significantly improved.

Ključne riječi

continuous casting; breakout prediction; temperature; neural network; mean square error(MSE)

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