Modeling and Optimization Research of CFB-FGD Based on Improved Genetic Algorithms and BP Neural Network

Zhi Bo Ren; Lei Sun; Yao Deng

doi:10.4028/www.scientific.net/AMR.610-613.1601

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 610-613Modeling and Optimization Research of CFB-FGD...

Modeling and Optimization Research of CFB-FGD Based on Improved Genetic Algorithms and BP Neural Network

Abstract:

In order to improve the efficiency of CFB-FGD (circulated fluidized bed for flue gas desulfurization) in many thermal power plants, this paper used the improved genetic algorithms and BP neural network to model and optimize the operation of CFB-FGD. First, this paper build BP neural network model to simulate CFB-FGD. Then, based on this model, we used the improved genetic algorithms to optimize CFB-FGD. The results can help improve the efficiency of CFB-FGD and decrease enterprise operating costs.

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Periodical:

Advanced Materials Research (Volumes 610-613)

Pages:

1601-1604

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.610-613.1601

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Online since:

December 2012

Authors:

Zhi Bo Ren, Lei Sun, Yao Deng

Keywords:

BP Neural Network (BPNN), CFB-FGD, Genetic Algorithm (GA)

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References

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