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OALib Journal期刊
ISSN: 2333-9721
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基于自适应遗传算法的锅炉低nox燃烧建模及其优化
, PP. 60-64
Keywords: 电站锅炉,燃烧优化,nox排放,svm,自适应遗传算法
Abstract:
为了对锅炉nox排放进行优化控制,分析现场运行数据,建立了基于支持向量机(svm)的nox排放特性模型,采用改进的自适应遗传算法对模型参数进行寻优,并比较了基于sigmoid核函数和rbf核函数的svm模型的性能。结果表明,rbf核函数更具有优势,且svm算法有良好的泛化能力和预测精度。结合svm建模和自适应遗传算法寻优,对锅炉可调参数进行优化,使该炉的nox排放量从423mg/m3降低至219.4mg/m3,下降幅度达到了48.13%。通过上述方法可得到低nox排放的最佳运行参数组合,为电站锅炉的运行优化指导和nox排放控制提供参考和依据。
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