【摘要】 铜转炉吹炼终点预报是转炉生产的一个重要环节,直接影响转炉的生产效益。其吹炼工艺相当复杂,影响生产因素众多且因素之间相互耦合,使得用来预测吹炼终点的模型极其复杂。针对这个问题,利用主元分析法将影响因素重组,在此基础上,提出一种基于遗传算法的Elman神经网络模型对铜转炉吹炼终点进行预测。仿真结果表明,建立的预报模型具有较高的自学习及泛化能力,预报结果具有较高的精度。更多还原

【Abstract】 The endpoint prediction is one of the most important processes of converting furnace.It influences the benefit of the produce directly.The process of converting furnace is completely complex and coupled.To this question,principal component analysis(PCA) method was used to reorganize the factors.On this basis,the genetic algorithm(GA) was introduced by combining Elman neural network to predict the endpoint of converting furnace.The model was set up using MATLAB software.The simulation results show that the model possesses higher precision and practicability.更多还原