优化SVM在锅炉负荷预测中的应用

Qi-song CHEN,Xiao-wei CHEN,Xin ZHANG,Mao-nian WU

Dianzi Keji Daxue Xuebao/Journal of the University of Electronic Science and Technology of China（2010）

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Abstract

提出智能优化支持向量机算法来提高模型的预测能力和泛化能力.该算法针对支持向量机噪声敏感问题采用小波方法对数据集去噪;利用核主成分分析方法提取数据特征;采用量子粒子群算法优化支持向量机超参数.将该优化算法应用于锅炉负荷短期预测,实验结果表明,该优化算法预测精度较高,收敛速度较快,泛化性能优于其他预测方法,且工程实现容易.

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Key words

kernel principle component analysis,support vector machines,quantum-behaved particle swarm algorithm,optimization,forecasting

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