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OALib Journal期刊
ISSN: 2333-9721
费用：99美元
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基于pca？svr的燃煤锅炉nox排放预测
, PP. 87-90
Keywords: 燃煤锅炉,nox排放量,预测模型,主成分分析,支持向量机
Abstract:
以某超超临界700mw机组锅炉为对象,建立了基于主成分分析(pca)和支持向量回归(svr)的氮氧化物(nox)排放预测模型(pca-svr模型)。运用pca方法对包含有2000条锅炉运行记录的数据集进行分析,降低数据集维数,提取有效信息(主成分);以得到的主成分为输入变量,锅炉nox排放值为输出变量,利用svr建立nox预测模型。与传统svr模型相比,pca-svr模型的计算时间更短,并且能获得较高的nox排放预测精度,其预测nox排放浓度与实际排放浓度相比平均误差在1%以内。
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