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| Prediction Modeling Study for Blast Furnace Hot Metal Temperature Based on T-S Fuzzy Neural Network Model |
| CUI Gui-mei1，LI Jing1，ZHANG Yong1，LI Zhong-de1，MA Xiang2 |
1. School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou 014010,Nei Mongol, China
2. Iron Plant of Baotou Iron and Steel Company, Baotou 014010, Nei Mongol, China |
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Abstract According to the shortage of the positively relation of blast furnace temperature and hot metal silicon rather than strict linear relationship, the subjectivity of the modelling by mechanism,and mechanism model dificultly to estabish the connotative mathematic relation between every varables, the mass of the sample data was processed through preprocessing and feature extraction based on the theory of data mining, and then blast furnace hot metal temperature was deemed as the research object, blast furnace hot metal temperature prediction model was established based on T-S fuzzy neural network. And the model and T-S fuzzy regression model and BP neural network model were compared; Through using some blast furnace data for model test, simulation results show that T-S fuzzy neural network model performance is superior to other models.
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Received: 04 March 2013
Published: 25 November 2013
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2013, Vol. 48 
