电信网络运维分析与故障预测算法研究

文中旨在研究电信网络运维分析与故障预测算法，以提高电信网络的稳定性和可靠性。首先，通过收集大量的网络性能数据和故障记录，建立一个综合性的数据集。然后，提出了一种基于机器学习的故障预测模型，该模型利用了时间序列分析、特征工程和监督学习算法。实验结果表明，该模型在故障预测方面具有显著的优势，能提前识别潜在故障并采取相应的维护措施，从而降低网络故障的影响。最后，强调了故障预测算法在电信网络运维中的重要性，并为网络运维提供了有力的工具和方法。

Research on Telecommunication Network Operation and Maintenance Analysis and Fault Prediction Algorithm

This paper aims to study telecom network operations and fault prediction algorithms to enhance the stability and reliability of telecommunication networks. Firstly, establishs a comprehensive dataset by collecting a large volume of network performance data and fault records.Then, proposes a machine learning-based fault prediction model that utilizes time series analysis, feature engineering, and supervised learning algorithms. Experimental results demonstrate that the model exhibits significant advantages in fault prediction, enabling early identification of potential issues and the implementation of corresponding maintenance measures, thereby reducing the impact of network failures. Finally, emphasize the importance of fault prediction algorithms in telecom network operations and provides powerful tools and methods for network maintenance.