基于时间序列算法的网络设备故障预测模型

Network Equipment Fault Prediction Model Based on Time Series Algorithm

随着网络设备在各个行业的广泛应用,对网络设备的可靠性和稳定性要求也越来越高,因此网络设备故障预测成为网络运维管理的重点。为了对网络设备故障进行预测,利用时间序列算法,构建了网络设备故障预测模型。首先,分析了自回归差分移动平均(ARIMA)模型的特点;然后,提出了ARIMA模型时间序列预测步骤,包括模型分析、算法建模和模型检验与评估;最后,通过案例分析验证了ARIMA模型的有效性和准确性。

With the wide application of network equipment in various industries,the reliability and sta⁃bility of network equipment are increasingly required.The network equipment fault prediction has be⁃come the focus of network operation and maintenance management.In order to predict the fault of net⁃work equipment,a network equipment fault prediction model is constructed by using time series algo⁃rithm.Firstly,the characteristics the autoregressive integrated moving average(ARIMA)model are analyzed.Then,the time series prediction steps of ARIMA model are proposed,including the model analysis,the algorithm modeling,and the model testing and evaluation.Finally,the validity and accu⁃racy of ARIMA model are analyzed and verified by the case application.