Neural Network-Based Intelligent Integrated Modeling for the CFB-FGD Process,10.1109/WCICA.2006.1713271,Li Hongru,Fan Liting,Wang Fuli

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


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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

Published in 2006.

DOI: 10.1109/WCICA.2006.1713271

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Keywords (6)

Neural Network-Based Intelligent Integrated Modeling for the CFB-FGD Process,10.1109/WCICA.2006.1713271,Li Hongru,Fan Liting,Wang Fuli

References (5)

Model for flue-gas desulfurization in a circulating dry scrubber (Citations: 17)

Gas phase hydrodynamics in the riser of a circulating fluidized bed (Citations: 24)

Modeling and experimental studies of SO 2 absorption in coaxial cylinders with impinging streams: Part I (Citations: 23)

Development of a neural network model for a cold rolling process (Citations: 19)

Model identification of nonlinear time variant processes via artificial neural network (Citations: 12)


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