Abstract
According to the evaluation and control of energy-saving and emission reduction performance of coal-fired boilers, the performance indexes of boiler combustion and emissions were studied, and a performance evaluation and control method based on neural network was proposed. Firstly, the influencing factors of boiler combustion emission are analyzed. A boiler combustion emission evaluation model based on AdaBoost-BP algorithm is designed. The model is trained and tested by coal-fired power plant data and national emission standards, and the principal component analysis method is adopted. The core parameters are adjusted to get the best control solution. Finally, experiments show that the model and method have better advantages in comparison with similar methods.
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Acknowledgements
This work is supported by the Social Science Planning Project in Fujian Province Project (FJ2016C133), the Scientific Research Foundation for Young and Middle-aged Teachers of Fujian Province (JZ160163) and the Fujian Province Education Science “13th Five-Year Plan” Project (FJJKCG16-289).
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Chen, Y., Xiao, L., Hosam, O. (2019). A Performance Evaluation Method of Coal-Fired Boiler Based on Neural Network. In: Qiu, M. (eds) Smart Computing and Communication. SmartCom 2019. Lecture Notes in Computer Science(), vol 11910. Springer, Cham. https://doi.org/10.1007/978-3-030-34139-8_27
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DOI: https://doi.org/10.1007/978-3-030-34139-8_27
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