Breakout prediction for continuous casting using genetic algorithm-based back propagation neural network model
by Benguo Zhang; Ruizhong Zhang; Ge Wang; Lifeng Sun; Zhike Zhang; Qiang Li
International Journal of Modelling, Identification and Control (IJMIC), Vol. 16, No. 3, 2012

Abstract: In this paper, the effectiveness of the genetic algorithm-based back propagation (GABP) neural network model and its application to the breakout prediction in the continuous casting process are investigated. The formation of the sticking-type breakouts and the prediction principle of thermocouple thermometry method are analysed firstly. Then the genetic algorithm-based back propagation neural network model is proposed by fusing genetic algorithm (GA), and error back propagation neural network to offset the demerits of one paradigm by the merits of another. Finally, the GABP neural network model is applied to the breakout prediction in the continuous casting process; and the feasibility of the model is verified by the testing result with the accuracy rate of 97.56% and the prediction rate of 100%.

Online publication date: Wed, 17-Dec-2014

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