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RECURSIVE NEURAL NETWORKS AND ITS APPLICATION IN FORECASTING THE STATE OF ELECTRIC POWER EQUIPMENT

机译:递归神经网络及其在电力设备状态预测中的应用

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This paper proposes a method based on the recursive neural network rather than the usual BP algorithm.A three -layer BP network structure with input layer, hidden layer, and output layer is used.The inputs are resistance leak current of continuous time sequence, and the values behind are outputs; after the training and learning according to the recursive neural network algorithm, the state forecast of MOA is realized.The result indicates that recursive network is more adapted to the state forecast of MOA.
机译:本文提出了一种基于递归神经网络的方法,而不是通常的BP算法。采用输入层,隐藏层和输出层的三层BP网络结构,输入为连续时间序列的电阻泄漏电流,后面的值是输出;经过递归神经网络算法的训练和学习,实现了MOA的状态预测。结果表明,递归网络更适合于MOA的状态预测。

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