Application Analysis of Machine Learning in Intelligent Operation and Maintenance System

Jin Jubo, Wan Abdul Malek Wan Abdullah, Zhiyuan Chen, Norizan Binti Anwar
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Abstract

The traditional operation and maintenance platform is dependent on the static rules set manually, which can not better cope with the dynamic and complex changing scene. Nowadays, with the rapid development of machine learning and artificial intelligence, intelligent operation and maintenance system can make more efficient and accurate decisions in the face of dynamic changing scenarios through big data accumulated in business scenarios, and can also automatically monitor services, detect abnormal events, and deal with faults in emergency. This paper carefully analyzes the necessity of constructing an intelligent operation and maintenance system, and the application of machine learning in the analysis and fault detection of intelligent operation and maintenance system.
机器学习在智能运维系统中的应用分析
传统的运维平台依赖于手工设置的静态规则,不能较好地应对动态、复杂的变化场景。如今,随着机器学习和人工智能的快速发展,智能运维系统可以通过业务场景积累的大数据,在面对动态变化的场景时做出更高效、准确的决策,并可以自动监控业务、检测异常事件、处理紧急故障。本文详细分析了构建智能运维系统的必要性,以及机器学习在智能运维系统分析与故障检测中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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