Intelligent predictive model of ventilating capacity of imperial smelt furnace

来源期刊：中南大学学报(英文版)2003年第4期

论文作者：唐朝晖 胡燕瑜 桂卫华 吴敏

文章页码：364 - 368

Key words：imperial smelt furnace; ventilating capacity; intelligent predictive model; artificial neural network; gray theory; adaptive fuzzy combination

Abstract: In order to know the ventilating capacity of imperial smelt furnace(ISF), and increase the output of plumbum, an intelligent modeling method based on gray theory and artificial neural networks(ANN) is proposed, in which the weight values in the integrated model can be adjusted automatically. An intelligent predictive model of the ventilating capacity of the ISF is established and analyzed by the method. The simulation results and industrial applications demonstrate that the predictive model is close to the real plant, the relative predictive error is 0.72%, which is 50% less than the single model, leading to a notable increase of the output of plumbum.