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A Hybrid Support Vector Fuzzy Inference System for the Classification of Leakage Current Waveforms Portraying Discharges

机译:用于描述放电的漏电流波形分类的混合支持向量模糊推理系统

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摘要

Several techniques have been applied on leakage current waveforms in order to extract information regarding electrical activity on high-voltage insulators. However, a fully representative value is yet to be defined. In this article, a hybrid support vector fuzzy inference system is introduced as a classification tool. The system incorporates fuzzy logic, genetic algorithms, and support vector machines. Apart from the classification accuracy achieved, the system also produces a set of fuzzy rules under which the classification is made, allowing a further insight of the process. A comparison is made to other classification tools previously applied on the same data set.
机译:为了提取有关高压绝缘子上电活动的信息,已经对泄漏电流波形应用了几种技术。但是,尚未定义完全具有代表性的值。在本文中,引入了一种混合支持向量模糊推理系统作为分类工具。该系统结合了模糊逻辑,遗传算法和支持向量机。除了实现分类的准确性外,系统还生成一组模糊规则,可根据这些规则进行分类,从而进一步了解过程。与以前应用于同一数据集的其他分类工具进行了比较。

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