计算机应用研究
計算機應用研究
계산궤응용연구
APPLICATION RESEARCH OF COMPUTERS
2010年
4期
1427-1429
,共3页
告警序列%决策函数%核函数%稀疏贝叶斯%预测精度
告警序列%決策函數%覈函數%稀疏貝葉斯%預測精度
고경서렬%결책함수%핵함수%희소패협사%예측정도
alarm sequences%decision function%kernel function%sparse Bayesian%prediction accuracy
针对通信网告警中预示重大故障的告警数量少、不适合用传统预测方法的特点,提出了一种基于稀疏贝叶斯的通信告警序列预测方法(PBM),并与支持向量机(SVM)预测方法进行了比较.实验结果表明,PBM方法非常适用于小样本的通信告警预测,其不仅具有SVM的预测性能,而且在样本数目增加时的预测误差率要小于SVM,具有非常好的预测精度.
針對通信網告警中預示重大故障的告警數量少、不適閤用傳統預測方法的特點,提齣瞭一種基于稀疏貝葉斯的通信告警序列預測方法(PBM),併與支持嚮量機(SVM)預測方法進行瞭比較.實驗結果錶明,PBM方法非常適用于小樣本的通信告警預測,其不僅具有SVM的預測性能,而且在樣本數目增加時的預測誤差率要小于SVM,具有非常好的預測精度.
침대통신망고경중예시중대고장적고경수량소、불괄합용전통예측방법적특점,제출료일충기우희소패협사적통신고경서렬예측방법(PBM),병여지지향량궤(SVM)예측방법진행료비교.실험결과표명,PBM방법비상괄용우소양본적통신고경예측,기불부구유SVM적예측성능,이차재양본수목증가시적예측오차솔요소우SVM,구유비상호적예측정도.
The alarm which indicates major failure in communication networks has a small number, in this case it is not suitable for traditional forecasting methods. This paper proposed a PBM, and compared it to SVM estimate method. The results show that, PBM is applicable to the small sample of telecommunication alarms predict. It not only has the predict performance of SVM, but also has lower predict errors than SVM when the number of samples increase, even it has a very good prediction accuracy.