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A hybrid Adaline and Bacterial Foraging approach to power system harmonics estimation

机译:电力系统谐波估计的混合Adaline和细菌觅食方法

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Harmonics estimation for a signal distorted with additive noise is an interdisciplinary area of interest for many researchers. This paper presents Bacterial Foraging Optimization (BFO) for estimating the fundamental as well as harmonic components present in power system voltage waveforms. The basic foraging strategy is made more adaptive by updating the weights of Adaptive Linear Neural Networks (Adaline) on taking the initial weighs as output of BFO. Performance of this new algorithm is compared with that of existing BFO.
机译:对于具有附加噪声失真的信号,谐波估计是许多研究人员感兴趣的跨学科领域。本文介绍了细菌觅食优化(BFO),用于估计电力系统电压波形中存在的基波分量和谐波分量。通过将初始权重作为BFO的输出来更新自适应线性神经网络(Adaline)的权重,使基本觅食策略更具适应性。将该新算法的性能与现有BFO的性能进行了比较。

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