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一个毕业程序设计，是用小波和支持向量机对电能质量扰动的识别与分类，主要利用的能量特征。-A graduate program design is the use of wavelet and support vector machines for power quality disturbance recognition and classification, the main characteristics of energy use.
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一篇关于电能质量问题及其检测分类方法的外文文献，大家可以参考一下-Article on the detection of power quality problems and their classification of documents in foreign languages, we can refer to
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本文提出了一种自动检测和电能质量扰动分类模糊专家系统。有关干扰的类型包括电压骤降，骤升，中断，切换瞬变，冲动，闪烁，谐波和缺口。据推测，在所分析的波形采样的形式提供。傅立叶变换和小波分析，利用独特的功能获得的波形一个模糊专家系统为主体的决定有关的干扰类型而设计的。仿真研究，验证了该方法的比较研究人工神经网络为基础的分类方法和该方法研究的准确性也报告，以显示该方法的优点-This paper presents a fuzzy-expert system for automated detectio
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基于小波和支持向量机的电能质量监测分类算法例程-Based on wavelet and support vector machine classification algorithm routine power quality monitoring
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Power quality monitoring has advanced
to an important tool for system evaluation
and solving power-related problems. As a
consequence the increased amount of recorded
data requires more sophisticated analysis methods.
The paper proposes a s
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