A feature selection method, GRRF-A, based on guided regularized random forest is proposed in this paper, aiming at solving marine diesel engine fault problem. GRRF-A improves GRRF algorithm according to the characteristics of marine diesel engine by using mean decrease in accuracy as importance measure, which is proven to be effective. The computation cost of GRRF-A is small and its results are relatively accurate and stable, which makes this method more suitable for marine diesel engine diagnosis than other methods discussed in this paper.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Research on fault pattern analysis of marine diesel engine based on random forest algorithm


    Beteiligte:
    Wang, Xian-xin (Autor:in) / Han, Bing (Autor:in)


    Erscheinungsdatum :

    01.08.2017


    Format / Umfang :

    364554 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Research on Fault Diagnosis of Marine Diesel Engine Based on KFDA

    Chai, Yan-You / Peng, Xiu-Yan / Man, Xin-Jiang | Tema Archiv | 2012


    Research on fault prediction of marine diesel engine based on attention-LSTM

    Liu, Yi / Gan, Huibing / Cong, Yujin et al. | SAGE Publications | 2023


    Large marine diesel engine research

    Ducrot, M. | Engineering Index Backfile | 1940


    Real-time marine diesel engine simulation for fault diagnosis

    Logan, K. / Inozu, B. / Roy, P. et al. | Tema Archiv | 2002