摘要
随着电力通信网络规模越来越大,运行维护人员对通信网运行状态的实时有效监控,对设备故障的快速准确判断越来越困难,需要对通信网运行的健康状态进行科学评估,以及对网络性能的劣化进行趋势预测,从而可以提前预知网络可能存在的隐患。论文充分利用通信网现有的海量状态监测数据,提出基于健康状态数据的电力通信网性能劣化评估模型,在此基础上利用最小二乘支持向量机(LS-SVM)性能劣化时间序列进行预测,预警通信网的异常状态,提高通信网运行维护的水平,减少故障导致的断网损失。
With the increasing scale of power communication network,the operation and maintenance personnel are more and more difficult to effectively monitor the real-time operational status and accurately determine equipment failure.Therefore,it is necessary to study the health state evaluation and performance degradation trend prediction of communication network operation.In this paper,making full use of the existing mass communications network status monitoring data,power communication network performance evaluation model based on the deterioration of the health status of the data is proposed.On this basis,least squares support vector machine（LS-SVM）time series is used to forecast performance degradation,in order to timely complete the communication network abnormal state early warning,improve communication network operation and maintenance level,reduce the fault caused by the loss of the network.
出处
《计算机与数字工程》
2016年第4期610-614,共5页
Computer & Digital Engineering
关键词
电力通信网
劣化评估
预测模型
power communication network
degradation assessment
prediction model
