DocumentCode :
1706493
Title :
Research on modeling method of coke oven´s blast blower suction based on improved BP neural network
Author :
Weng Yongpeng ; Gao Xianwen ; Lv Mingyang ; Liu Xinming ; Wang Mingshun ; Wang Junsheng
Author_Institution :
Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
fYear :
2013
Firstpage :
1742
Lastpage :
1747
Abstract :
For the complicated mechanism and difficult traditional modeling of the blast blower cooling system of coke oven, a new dynamic mathematic model for the fore end suction of blast blower cooling system has been firstly established. This model avoids the complex process of analysis on blast blower cooling system, makes full use of the existing field data, and traverses to all sections of the production process. Then artificial bee colony (ABC) algorithm is used to optimize the BP neural network´s structure parameters and an analysis is conducted on different type of input variables. Finally, a validation for the established model is performed with the test samples that collected from different process sections, and simulation results show that the obtained model has a faster convergence and higher approximation accuracy.
Keywords :
ant colony optimisation; backpropagation; cooling; neural nets; ovens; production engineering computing; ABC algorithm; approximation accuracy; artificial bee colony algorithm; backpropagation neural network; blast blower cooling system; coke oven blast blower suction; convergence; dynamic mathematic model; fore end suction; improved BP neural network; input variables; Algorithm design and analysis; Analytical models; Cooling; Data models; Mathematical model; Neural networks; Ovens; BP neural network; accuracy; artificial bee colony algorithm; coke oven´s blast blower cooling system; fore end suction model of the coke oven´s blast blower;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2013 32nd Chinese
Conference_Location :
Xi´an
Type :
conf
Filename :
6639708
Link To Document :
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