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Wavelet neural network based on compound model PSO with stochastic inertia weight and its application in choosing tested positions of gearbox

机译:基于随机惯性权重的复合模型PSO的小波神经网络及其在齿轮箱测试位置选择中的应用

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Compound model PSO with stochastic inertia weight is put forward and used to optimize the parameters of wavelet neural network. The trained wavelet neural-network is applied to choosing tested position of gearbox. It is an available approach to solve the problems on choosing tested position in fault diagnosis.
机译:提出了具有随机惯性权重的复合模型粒子群优化算法,并将其用于小波神经网络参数的优化。训练后的小波神经网络被应用于选择变速箱的测试位置。它是解决故障诊断中选择被测位置时存在问题的一种可行方法。

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