基于微分进化的钢水温度预报混合模型

针对LF冶炼过程钢水温度预报问题对机理模型进行了分析.将基于微分进化的BP网络引入混合模型,以确定模型中难以准确获得的参数,建立了基于微分进化的钢水温度混合预报模型.模型通过适当时刻变异因子的随机选取和重复进行种群个体初始化的方法,对微分进化算法进行了改进,有效解决了BP网络训练的困难,避免了算法早熟.实验结果表明,混合模型具有较好的预测结果,基本满足了实际生产的需要.

Hybrid Modeling Based on Differential Evolutionary Algorithm for Prediction of Molten Steel Temperature

To predict the molten steel temperature in the smelting process of ladle furnace(LF),a hybrid model is proposed,where a BP neural network trained by an improved differential evolutionary algorithm(DEA) is introduced to determine the model parameters which are hard to exactly obtain by mechanism models.In the model,the mutation factor is randomly selected and the individuals in population are re-initialized in due time,thus rising above the difficulty efficiently in training BP neural network and avoiding th...