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Comparison of some neural network algorithms used in prediction of XLPE HV insulation properties under thermal aging

机译:预测热老化下XLPE高压绝缘性能的几种神经网络算法的比较

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Some Artificial neural network algorithms have been used to predict properties of high voltage electrical insulation under thermal aging in term to reduce the aging experiment time. In this paper we present a short comparison of the obtained results in the case of Cross-linked Polyethylene (XLPE). The theoretical and the experimental results are concordant. As a neural network application, we propose a new method based on Radial Basis Function Gaussian network (RBFG) trained by two algorithms: Random Optimization Method (ROM) and Back-propagation (BP).
机译:一些人工神经网络算法已被用于预测热老化条件下的高压电绝缘性能,以减少老化实验时间。在本文中,我们将对交联聚乙烯(XLPE)情况下获得的结果进行简短比较。理论和实验结果是一致的。作为一种神经网络应用,我们提出了一种基于径向基函数高斯网络(RBFG)的新方法,该算法由以下两种算法训练:随机优化方法(ROM)和反向传播(BP)。

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