基于机器学习算法的网站维护告警识别系统设计与实现  

Design and Implementation of Website Maintenance Alarm Recognition System Based on Machine Learning Algorithms

作　　者：孙滨[1] 杨民声[1] SUN Bin;YANG Minsheng(Tai’an City Central Hospital,Tai’an Shandong 271000,China)

机构地区：[1]泰安市中心医院,山东泰安271000

出　　处：《信息与电脑》2024年第11期99-102,共4页Information & Computer

摘　　要：本论文旨在设计并实现一种基于机器学习算法的网站维护告警识别系统,以解决当前网站管理中存在的数据离散问题,提高管理效率和效果。针对网站维护过程中出现的大量告警信息,文章提出了一套告警日志分析识别系统,通过有效地从无用告警信息中提取出重要的告警信息,实现对网站维护者的实时预警。在系统架构设计中,本研究使用了决策树(Decision Trees,DT)、支持向量机(Support Vector Machine,SVM)和梯度提升树(Gradient Boosting Tree,GBT)等机器学习算法对告警日志进行分析和建模,并通过实验验证了梯度提升树模型在识别有效告警方面的最佳性能。最终选择的系统能够帮助网站管理者及时发现和处理重要的系统异常或错误事件,提高网站的稳定性和可靠性。This paper aims to design and implement a website maintenance alarm recognition system based on machine learning algorithms to address the current issue of data disparity in website management and enhance its efficiency and effectiveness.To tackle the plethora of alarm signals encountered during website maintenance,the paper proposes an alarm log analysis and recognition system,enabling the extraction of crucial alarm signals from the noise for real-time alerting of website administrators.In the system architecture design,the study employs machine learning algorithms such as Decision Trees(DT),Support Vector Machines(SVM)and Gradient Boosting Trees(GBT)to analyze and model alarm logs,validating through experiments the superior performance of the gradient boosting tree model in identifying significant alarms.The ultimately chosen system aids website administrators in promptly identifying and addressing critical system anomalies or errors,thereby improving website stability and reliability.

关 键 词：机器学习 网站维护 告警识别系统 告警日志分析 

分 类 号：TP393.092[自动化与计算机技术—计算机应用技术]