(中南大学 信息科学与控制工程学院，长沙 410083)
摘 要: 以密闭鼓风炉熔炼过程为研究对象， 采用自适应组合集成技术将神经网络NN和灰色理论有机结合的方法建立了密闭鼓风炉透气性预测模型。 仿真和工业应用结果表明： 所提出的模型能很好地实现密闭鼓风炉透气性的预测，并能使铅锌产量得到显著的提高。
关键字: 密闭鼓风炉熔炼过程； 透气性； 预测模型； 神经网络； 灰色理论； 自适应模糊组合
furnace breathing capacity
（College of Information Science & Engineering,
Central South University, Changsha 410083, China）
Abstract:Based on gray theory and neural network, the breathing capacity predication model of an imperial blast furnace was constructed by self-adaptive integration technology according to the melting process in an imperial blast furnace. Simulation and industry application results show that the predictive model can realize accurate predication of the breathing capacity for imperial blast furnace, which leads to a notable increase of plumbum and zinc output.
Key words: imperial blast furnace melting process; breathing capacity; predictive model; neural networks; gray theory; self-adaptive fuzzy combination
