基于BP神经网络的交流输电线路可听噪声预测模型

可听噪声属于输电线路电磁环境的影响因子之一,其常规预测模型均存在使用条件受约束或预测误差偏大的问题.根据间接预测法的思想,以可听噪声通用表达式中的4个因素为输入变量,可听噪声值为输出变量,建立了三层结构的BP神经网络交流输电线路可听噪声预测模型.以国外多条输电线路可听噪声数据为样本,通过BP神经网络对样本进行训练,运用得到的模型对预测集线路的可听噪声值进行了预测.结果表明,与常规GE公式相比,采用BP神经网络预测模型的预测平均绝对误差要小1.641 4 d B(A).

Audible Noise Prediction Model of AC Power Lines Based on BP Neural Network

Audible noise is one of impact factors for power line electromagnetic environment. Nevertheless,there are the problems for application constraints and unacceptable errors in the traditional prediction models. According to the theoretical of the indirect method,an audible noise prediction model with a structure of three layers for AC transmission lines was established based on BP neural network,in which the input variables are four factors in general expression of audible noise and the output variable is audible noise value. Taking audible noise dates of abroad multiple transmission lines as an example,a train was acquired from the training dataset through BP neural network. Using the trained model,the audible noise values were predicted for the transmission lines in prediction dataset. The results showed that the value of the mean absolute error,which was predicted by the proposed model based on BP neural network,was 1. 641 4 d B( A) which is less than that of GE formula.