李静雅;曹洁;姜梅;

• 1:兰州理工大学计算机与通信学院
• 2:甘肃电力科学研究院

摘要(Abstract)：

以甘肃省多条330 kV超高压输电线路可听噪声的实测数据样本为例,研究基于误差反传(back propagation,BP)神经网络的可听噪声预测的方法。将330 kV单回路三角型线路结构输电线路的可听噪声数据整理分析后建立数据样本,选择影响可听噪声的13个因素作为输入变量,可听噪声值作为输出变量,建立3层结构的BP神经网络预测模型,用数据样本训练和验证预测模型。结果表明,基于BP神经网络的可听噪声预测方法能够较精确地预测可听噪声数据样本中除了输入样本以外的其余样本,可作为超高压输电线路可听噪声预测的一种简单有效的方法。

关键词(KeyWords)： 超高压输电线路;实测数据;单回路三角线路结构;可听噪声预测;BP神经网络

Abstract:

Keywords:

基金项目(Foundation):

作者(Author): 李静雅;曹洁;姜梅;

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参考文献(References)：

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