Intelligent predictive model of ventilating capacity of imperial smelt furnace

被引：1

作者：

Zhao-hui Tang

Yan-yu Hu

Wei-hua Gui

Min Wu

机构：

[1] Central South University,School of Information Science and Engineering

来源：

Journal of Central South University of Technology | 2003年 / 10卷

关键词：

imperial smelt furnace; ventilating capacity; intelligent predictive model; artificial neural network; gray theory; adaptive fuzzy combination; TP278; TF813;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

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.

引用

页码：364 / 368

页数：4

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