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Volumn 7, Issue Special Issue 6, 2016, Pages

Combining deep learning and survival analysis for asset health management

Author keywords

[No Author keywords available]

Indexed keywords


EID: 84988952865     PISSN: None     EISSN: 21532648     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (32)

References (13)
  • 3
    • 84925292228 scopus 로고    scopus 로고
    • Health assessment and life prediction of cutting tools based on support vector regression
    • Benkedjouh, T., Medjaher, K., Zerhouni, N., & Rechak, S. (2015). Health assessment and life prediction of cutting tools based on support vector regression. Journal of Intelligent Manufacturing, 26(2), 213–223.
    • (2015) Journal of Intelligent Manufacturing , vol.26 , Issue.2 , pp. 213-223
    • Benkedjouh, T.1    Medjaher, K.2    Zerhouni, N.3    Rechak, S.4
  • 4
    • 0000193853 scopus 로고
    • On gibbs sampling for state space models
    • Carter, C. K., & Kohn, R. (1994). On gibbs sampling for state space models. Biometrika, 81(3), 541–553.
    • (1994) Biometrika , vol.81 , Issue.3 , pp. 541-553
    • Carter, C.K.1    Kohn, R.2
  • 5
    • 0034293152 scopus 로고    scopus 로고
    • Learning to forget: Continual prediction with lstm
    • Gers, F. A., Schmidhuber, J., & Cummins, F. (2000). Learning to forget: Continual prediction with lstm. Neural computation, 12(10), 2451–2471.
    • (2000) Neural Computation , vol.12 , Issue.10 , pp. 2451-2471
    • Gers, F.A.1    Schmidhuber, J.2    Cummins, F.3
  • 6
    • 85027917035 scopus 로고    scopus 로고
    • An adaptive method for health trend prediction of rotating bearings
    • Hong, S., Zhou, Z., Zio, E., & Wang, W. (2014). An adaptive method for health trend prediction of rotating bearings. Digital Signal Processing, 35, 117–123.
    • (2014) Digital Signal Processing , vol.35 , pp. 117-123
    • Hong, S.1    Zhou, Z.2    Zio, E.3    Wang, W.4
  • 8
    • 84903145771 scopus 로고    scopus 로고
    • Intelligent prognostics for battery health monitoring using the mean entropy and relevance vector machine. Systems, Man, and Cybernetics: Systems
    • Li, H., Pan, D., & Chen, C. P. (2014). Intelligent prognostics for battery health monitoring using the mean entropy and relevance vector machine. Systems, Man, and Cybernetics: Systems, IEEE Transactions on, 44(7), 851-862.
    • (2014) IEEE Transactions On , vol.44 , Issue.7 , pp. 851-862
    • Li, H.1    Pan, D.2    Chen, C.P.3
  • 9
    • 84966322221 scopus 로고    scopus 로고
    • Study on signal recognition and diagnosis for spacecraft based on deep learning method
    • Li, K., & Wang, Q. (2015). Study on signal recognition and diagnosis for spacecraft based on deep learning method. In Prognostics and system health management conference (phm), 2015 (pp. 1–5).
    • (2015) Prognostics and System Health Management Conference (Phm) , vol.2015 , pp. 1-5
    • Li, K.1    Wang, Q.2
  • 10
    • 84946615395 scopus 로고    scopus 로고
    • State of health estimation combining robust deep feature learning with support vector regression
    • Qiao, L. Q., & Xun, L. J. (2015). State of health estimation combining robust deep feature learning with support vector regression. In Control conference (ccc), 2015 34th chinese (pp. 6207–6212).
    • (2015) In Control Conference (Ccc), 2015 34Th Chinese , pp. 6207-6212
    • Qiao, L.Q.1    Xun, L.J.2
  • 11
    • 84875848937 scopus 로고    scopus 로고
    • Failure diagnosis using deep belief learning based health state classification
    • Tamilselvan, P., & Wang, P. (2013). Failure diagnosis using deep belief learning based health state classification. Reliability Engineering & System Safety, 115, 124–135.
    • (2013) Reliability Engineering & System Safety , vol.115 , pp. 124-135
    • Tamilselvan, P.1    Wang, P.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.