摘要
在统计学习理论框架下产生的支持向量机这一新的通用机器学习方法,能较好地解决小样本、非线性、高维数和局部极小点等实际问题,已成为机器学习界的研究热点之一。文章归纳了支持向量机在电力系统故障诊断、暂稳分类、负荷预测、谐波分析等方面的应用现状,并提出了可能进一步应用的方面。
Support vector machine(SVM) is a novel algorithm of machine learning based on statistical learning theory(SLT).SVM can better solve such practical problems as small samples,nonlinearity,high dimensionality and local minimization,which has become one of the concerns in machine learning world.The applications of SVM to the aspects such as fault diagnosis,transient stability classification,load forecast and harmonic analysis in power system are generalized in this article.In the meantime other potential aspects that SVM could be further applied to are presented here.
出处
《扬州职业大学学报》
2007年第2期31-34,62,共5页
Journal of Yangzhou Polytechnic College
关键词
统计学习理论
支持向量机
电力系统
statistical learning theory
support vector machine
power systems
