DocumentCode :
3730901
Title :
An integrated prediction model of sinter comprehensive performance
Author :
Kailu Lu; Fei Qiao; Yumin Ma
Author_Institution :
College of Electronics & Information Engineering, Tongji University, Shanghai, China
fYear :
2015
Firstpage :
298
Lastpage :
302
Abstract :
The process of sinter have a great influence on production and economic benefits of the iron-making, the prediction of sinter performance is very necessary. However, the sinter process is complex, nonlinear and hysteresis, and strong coupling, it´s impossible to establish a mathematical model. In this paper, we constructed a prediction model of sinter comprehensive performance by integrating GM(1,1) and BPNN based on information entropy since a single model can´t suit different sinter quality. The application results show that the prediction model has high accuracy rate, stability and efficiency.
Keywords :
"Predictive models","Data models","Support vector machines","Information entropy","Mathematical model","Temperature","Neural networks"
Publisher :
ieee
Conference_Titel :
Chinese Automation Congress (CAC), 2015
Type :
conf
DOI :
10.1109/CAC.2015.7382514
Filename :
7382514
Link To Document :
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