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ANFIS approach for noise reduction of lightning current online monitoring system

机译:ANFIS降低雷电流在线监测系统噪声的方法

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A novel de-noising algorithm, based on adaptive neural-fuzzy inference system (ANFIS) is proposed for noise reduction of the lightning current online monitoring system. The paper presents the theory and the implement procedure of the fuzzy neural system. Comparisons among the traditional strategies, such as curve fitting (CF), wavelet transform (WT) methods and the proposed ANFIS strategy are carried out. The simulation results demonstrate the superiority of the proposed method. Moreover, the employed approach has been tested on the practical measured current of lightning current online monitoring system. The testing results validate the proposed approach.
机译:提出了一种基于自适应神经模糊推理系统(ANFIS)的降噪算法,用于降低雷电在线监测系统的噪声。介绍了模糊神经系统的理论和实现过程。进行了传统策略的比较,例如曲线拟合(CF),小波变换(WT)方法和拟议的ANFIS策略。仿真结果证明了该方法的优越性。此外,所采用的方法已经在雷电电流在线监测系统的实际测量电流上进行了测试。测试结果验证了该方法的有效性。

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