Neural Network-Based Intelligent Integrated Modeling for the CFB-FGD Process

Author

Li Hongru ; Liting, Fan ; Fuli, Wang

Author_Institution

Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang

Volume

1

fYear

0

fDate

0-0 0

Firstpage

4686

Lastpage

4690

Abstract

The integration modeling method based on input weighted feed-forward neural network was proposed under the intelligent integrated modeling theory. According to the mechanism model of circulated fluidized bed for flue gas desulfurization(CFB-FGD), the influencing factor of sulfur dioxide removal was confirmed. Furthermore, depending on the effect of influencing factor, weighting coefficients of each factor were got and the intelligent integrated model based on neural network was set up. The simulation results indicate that the integrated model can simulate and predict the desulfurization efficiency perfectly, and is better than the mechanism model

Keywords

feedforward neural nets; flue gas desulphurisation; fluidised beds; process control; sulphur compounds; circulated fluidized bed; feedforward neural network; flue gas desulfurization; intelligent integrated modeling theory; sulfur dioxide removal; Environmental factors; Feedforward neural networks; Feedforward systems; Flue gases; Fluidization; Information science; Intelligent networks; Neural networks; Predictive models; Spraying; CFB-FGD; intelligent integrated model; mechanism model; neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1713271

Filename

1713271