现代信息科技2024，Vol.8Issue(1)：99-103,5.DOI:10.19850/j.cnki.2096-4706.2024.01.020
基于LSTM神经网络算法互联网电视EPG业务隐患预测的应用研究
Application Research on Prediction of Hidden Dangers in Internet Television EPG Business Based on LSTM Neural Network Algorithm
班雪飞 1倪峰 1周玮 1马占婕 1孙忠岩1
作者信息
- 1. 中国移动通信集团内蒙古有限公司,内蒙古 呼和浩特 010010
- 折叠
摘要
Abstract
With the deepening of the integration of the triple play and the development of smart Internet of Things technology,home broadband and internet television have become a new entry point for smart homes.In order to solve the problem of congenital lag in the timing of internet television business quality monitoring methods that cannot detect hidden faults before users,a LSTM neural network algorithm is introduced to achieve data injection intelligence business operation and maintenance capabilities.It focuses on the quality of EPG business services,identifies anomalies from business historical fluctuations and making predictive early warnings,and achieves the identification and prediction of EPG business quality hidden dangers.The length of hidden dangers discovery time is reduced to 0.5 hours,and the timely and accurate rates of hidden danger identification are above 90%.关键词
互联网电视/EPG业务质量/LSTM算法/隐患预测Key words
internet TV/EPG business quality/LSTM algorithm/prediction of hidden dangers分类
信息技术与安全科学引用本文复制引用
班雪飞,倪峰,周玮,马占婕,孙忠岩..基于LSTM神经网络算法互联网电视EPG业务隐患预测的应用研究[J].现代信息科技,2024,8(1):99-103,5.
