基于DE-BP神经网络的电力通信设备运行状态评估  

Evaluation of Operational Status of Power Communication Equipment Based on DE-BP Neural Network

作　　者：李玉 LI Yu

机构地区：[1]国网陕西省电力有限公司榆林供电公司,陕西榆林719100

出　　处：《今日自动化》2024年第9期170-172,共3页Automation Today

摘　　要：为科学量化评价变电站通信设备的运行状态,提出了一种基于DE–BP神经网络的电力通信设备运行状态评估模型。针对BP神经网络收敛速度慢和泛化能力弱等问题,引入差分进化算法优化神经网络的网络参数。试验数据表明,改进后的BP神经网络评估误差较小,能有效应用于电力通信设备运行状态评估分析。In order to scientifically quantify the operational status of communication equipment in substations,a power communication equipment operational status evaluation model based on BP neural network is proposed.In response to the problems of slow convergence speed and weak generalization ability of BP neural network,differential evolution algorithm is introduced to optimize the network parameters of the neural network.The experimental data shows that the improved BP neural network has small evaluation errors and can be effectively applied to the evaluation and analysis of the operating status of power communication equipment.

关 键 词：电力通信设备 运行状态评估 BP神经网络 差分进化算法 

分 类 号：TM63[电气工程—电力系统及自动化]