Modeling and Optimization of Coal Moisture Control System Based on BFO

被引：0

作者：

Li, Xiaobin ^{[1
]}

Hu, Ting ^{[1
]}

Yu, Yang ^{[1
]}

Sun, Haiyan ^{[1
]}

机构：

[1] Shanghai Inst Technol, Sch Elect & Elect Engn, Shanghai, Peoples R China

来源：

PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON ELECTRIC AND ELECTRONICS | 2013年

关键词：

coal moisture control; BFO; modeling; optimization;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

Coal moisture control process is a critical process in energy saving, pollution reduction and improving production efficiency and the quality of coke. To achieve precise control of coal moisture control system, against their strong coupling, large, nonlinear systems with time-delay characteristics using the RBF artificial neural network approach for modeling. And use the bionic BFO (Bacterial Foraging Optimization) according to the fitness to optimize the RBF Neural network parameters. Also compare the RBF Neural network performance optimized by these bionic BFO in order to achieve better results. This method provides a theoretical basis for accurate control of coal moisture process. To created the conditions for the reduction of energy and pollution with improving the quality of coke.

引用

页码：269 / 274

页数：6

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