海军航空工程学院学报
海軍航空工程學院學報
해군항공공정학원학보
JOURNAL OF NAVAL AERONAUTICAL ENGINEERING INSTITUTE
2013年
2期
154-160
,共7页
故障诊断%故障预测%相关向量机%机器学习
故障診斷%故障預測%相關嚮量機%機器學習
고장진단%고장예측%상관향량궤%궤기학습
fault diagnosis%fault prognosis%relevance vector machine%machine learning
相关向量机(RVM)是一种基于稀疏Bayesian学习理论的新型机器学习方法,具有概率式输出、稀疏性强、参数设置简单、核函数选择灵活等优点,克服了人工神经网络(ANN)和支持向量机(SVM)等典型机器学习方法的诸多固有缺陷.文章从模型选择与优化、模型计算效率和模型鲁棒性改进3个方面综述了RVM的理论研究进展;总结了RVM在故障诊断与预测中的应用研究现状;分析指出了当前研究中存在的问题,并讨论了基于RVM的故障诊断与预测技术的研究方向.
相關嚮量機(RVM)是一種基于稀疏Bayesian學習理論的新型機器學習方法,具有概率式輸齣、稀疏性彊、參數設置簡單、覈函數選擇靈活等優點,剋服瞭人工神經網絡(ANN)和支持嚮量機(SVM)等典型機器學習方法的諸多固有缺陷.文章從模型選擇與優化、模型計算效率和模型魯棒性改進3箇方麵綜述瞭RVM的理論研究進展;總結瞭RVM在故障診斷與預測中的應用研究現狀;分析指齣瞭噹前研究中存在的問題,併討論瞭基于RVM的故障診斷與預測技術的研究方嚮.
상관향량궤(RVM)시일충기우희소Bayesian학습이론적신형궤기학습방법,구유개솔식수출、희소성강、삼수설치간단、핵함수선택령활등우점,극복료인공신경망락(ANN)화지지향량궤(SVM)등전형궤기학습방법적제다고유결함.문장종모형선택여우화、모형계산효솔화모형로봉성개진3개방면종술료RVM적이론연구진전;총결료RVM재고장진단여예측중적응용연구현상;분석지출료당전연구중존재적문제,병토론료기우RVM적고장진단여예측기술적연구방향.
@@@@Relevance vector machine (RVM) is a new machine learning method based on sparse Bayesian learn?ing theory, which has probabilistic outputs, high sparsity, simple parameter tuning and flexible selection of ker?nel function. RVM has overcome many inherent defects of typical machine learning methods, such as ANN and SVM. The research progress of relevance vector machine (RVM) was summarized in model selection and optimi?zation, model computational efficiency and model robustness improvement. The research status of applications of RVM in fault diagnosis and prognosis was introduced. The existing problems in the current research were ana?lyzed and the development trends of fault diagnosis and prognosis based on RVM were discussed.