메뉴 건너뛰기




Volumn 28, Issue 5, 2007, Pages 1085-1090

Classification method of diverse AdaBoost-SVM and its application to fault diagnosis of aeroengine

Author keywords

Accuracy diversity; Adaboost; Aeroengine; Ensemble of classification methods; Fault diagnosis; SVM

Indexed keywords

ROTORS; SUPPORT VECTOR MACHINES;

EID: 35348941131     PISSN: 10006893     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (4)

References (10)
  • 1
    • 10444259853 scopus 로고    scopus 로고
    • Creating diversity in ensembles using artificial data
    • Melville P, Mooney R J. Creating diversity in ensembles using artificial data [J]. Information Fusion, 2005, 6(1): 99-111.
    • (2005) Information Fusion , vol.6 , Issue.1 , pp. 99-111
    • Melville, P.1    Mooney, R.J.2
  • 2
    • 0037403516 scopus 로고    scopus 로고
    • Measures of diversity in classifier ensembles and their relationship with ensemble accuracy
    • Kuncheva L I, Whitaker C J. Measures of diversity in classifier ensembles and their relationship with ensemble accuracy [J]. Machine Learning, 2003, 51(2). 181-207.
    • (2003) Machine Learning , vol.51 , Issue.2 , pp. 181-207
    • Kuncheva, L.I.1    Whitaker, C.J.2
  • 3
    • 0034250160 scopus 로고    scopus 로고
    • An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization
    • Dietterich T G. An experimental comparison of three methods for constructing ensembles of decision trees: bagging, boosting, and randomization [J]. Machine Learning, 2000, 40(2): 139-157.
    • (2000) Machine Learning , vol.40 , Issue.2 , pp. 139-157
    • Dietterich, T.G.1
  • 4
    • 6444238786 scopus 로고    scopus 로고
    • Selected tree classifier combination based on both accuracy and error diversity
    • Shin H W, Sohn S Y. Selected tree classifier combination based on both accuracy and error diversity. Pattern Recognition, 2005, 38: 191-197.
    • (2005) Pattern Recognition , vol.38 , pp. 191-197
    • Shin, H.W.1    Sohn, S.Y.2
  • 5
    • 35349003114 scopus 로고    scopus 로고
    • Classification method of AdaBoost based on SVM and its application in fault diagnosis of aeroengine
    • Chinese source
    • Hu Jinhai, Xie Shousheng, Yang Fan, et al. Classification method of AdaBoost based on SVM and its application in fault diagnosis of aeroengine [J]. Journal of Propulsion Technology (To be published), (in Chinese)
    • Journal of Propulsion Technology (To be published)
    • Hu, J.1    Xie, S.2    Yang, F.3
  • 7
    • 0003408496 scopus 로고    scopus 로고
    • UCI respository of machine learning database
    • Merz C, Murphy P. UCI respository of machine learning database [EB/OL]. 1998 [2006-5-25]. http://www.ics.uci.edu/-mlearn/MLRepository.html.
    • (1998)
    • Merz, C.1    Murphy, P.2
  • 9
    • 0142025124 scopus 로고    scopus 로고
    • Constructing support vector machine ensemble
    • Kim H C, Pang S N, Je H M, et al. Constructing support vector machine ensemble [J]. Pattern Recongnition, 2003, 36(12): 2757-2767.
    • (2003) Pattern Recongnition , vol.36 , Issue.12 , pp. 2757-2767
    • Kim, H.C.1    Pang, S.N.2    Je, H.M.3
  • 10
    • 0034243471 scopus 로고    scopus 로고
    • Boosting neural networks
    • Schwenk H, Bengio Y. Boosting neural networks [J]. Nuerul Computation, 2000, 12: 1869-1887.
    • (2000) Nuerul Computation , vol.12 , pp. 1869-1887
    • Schwenk, H.1    Bengio, Y.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.