A new online optimization method for boiler combustion system based on the data-driven technique and the case-based reasoning principle
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DOI: 10.1016/j.energy.2022.125508
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References listed on IDEAS
- Lv, You & Liu, Jizhen & Yang, Tingting & Zeng, Deliang, 2013. "A novel least squares support vector machine ensemble model for NOx emission prediction of a coal-fired boiler," Energy, Elsevier, vol. 55(C), pages 319-329.
- Aminmahalati, Alireza & Fazlali, Alireza & Safikhani, Hamed, 2021. "Multi-objective optimization of CO boiler combustion chamber in the RFCC unit using NSGA II algorithm," Energy, Elsevier, vol. 221(C).
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- Xu, Wentao & Huang, Yaji & Song, Siheng & Yue, Junfeng & Chen, Bo & Liu, Yuqing & Zou, Yiran, 2023. "A new on-line combustion optimization approach for ultra-supercritical coal-fired boiler to improve boiler efficiency, reduce NOx emission and enhance operating safety," Energy, Elsevier, vol. 282(C).
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Keywords
Online combustion optimization of boiler; Improved constrained fuzzy weighted rule; Improved multi-objective particle swarm optimization algorithm; Similarity measure -based case-based reasoning;All these keywords.
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