摘要
随着分布式系统的广泛应用,其稳定性和可靠性变得至关重要。作为保障分布式系统正常运行的关键环节,故障检测面临数据量大、检测速度与误报率要求高等挑战。针对分布式系统中的故障检测问题,文章提出了一种基于支持向量机(SVM)算法的故障检测方法,该方法通过引入特征选择和核函数优化提高了故障检测的准确性与效率。
With the widespread application of distributed systems,their stability and reliability have become crucial.As a key link in ensuring the normal operation of distributed systems,fault detection faces challenges such as large data volume,high requirements for detection speed and false alarm rate.This article proposes a fault detection method based on Support Vector Machine(SVM)algorithm for distributed systems,which improves the accuracy and efficiency of fault detection by introducing feature selection and kernel function optimization.
作者
杨涛
YANG Tao(Inner Mongolia Electronic Information Vocational and Technical College,Hohhot 010010,China)
出处
《计算机应用文摘》
2024年第17期183-185,共3页
Chinese Journal of Computer Application
关键词
分布式系统
故障检测
支持向量机
特征选择
核函数优化
distributed system
fault detection
support vector machine
feature selection
kernel function optimization
