基于支持向量机的电力通信网风险评估方法
Electric power communication network risk assessment method based on support vector machine
鉴于电力通信网风险评估的重要性,提出一种基于支持向量机的电力通信网风险评估方法。与其他风险评估方法相比,SVM一对一分类器对小样本测试环境的适应能力强,具有较好的分类准确率,能有效防止过学习的优点,通过分析分析当前电力通信网的风险因素,根据支持向量机理论和现有数据构造训练集和测试集,实现了对电力通信网风险的有效评估。
ue to the importance of the optical power communication network risk assessment, a kind of electric power communication network risk assessment method based on support vector machine (SVM) is proposed. Compared with other methods of risk assessment,the SVM one against one classifier for small sample test environment has good Strong adaptability、classification accuracy .At the same time ,it can effectively prevent the excessive learning.Through the analysis of the risk factors of the current optical power communication network, according to the theory of support vector machine (SVM) and existing data ,this paper build training set and test set, then assess the risks of the optical power communication network scientifically.
彭承晴、陈兴渝
输配电工程通信
电力通信网风险评估支持向量机
power communication networkrisk assessmentsupport vector machine
彭承晴,陈兴渝.基于支持向量机的电力通信网风险评估方法[EB/OL].(2014-12-16)[2025-08-03].http://www.paper.edu.cn/releasepaper/content/201412-441.点此复制
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