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An ensemble classifier to predict track geometry degradation

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  • Cárdenas-Gallo, Iván
  • Sarmiento, Carlos A.
  • Morales, Gilberto A.
  • Bolivar, Manuel A.
  • Akhavan-Tabatabaei, Raha

Abstract

Railway operations are inherently complex and source of several problems. In particular, track geometry defects are one of the leading causes of train accidents in the United States. This paper presents a solution approach which entails the construction of an ensemble classifier to forecast the degradation of track geometry. Our classifier is constructed by solving the problem from three different perspectives: deterioration, regression and classification. We considered a different model from each perspective and our results show that using an ensemble method improves the predictive performance.

Suggested Citation

  • Cárdenas-Gallo, Iván & Sarmiento, Carlos A. & Morales, Gilberto A. & Bolivar, Manuel A. & Akhavan-Tabatabaei, Raha, 2017. "An ensemble classifier to predict track geometry degradation," Reliability Engineering and System Safety, Elsevier, vol. 161(C), pages 53-60.
    • Handle: RePEc:eee:reensy:v:161:y:2017:i:c:p:53-60
    DOI: 10.1016/j.ress.2016.12.012
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    References listed on IDEAS

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    Cited by:

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    3. Sedghi, Mahdieh & Kauppila, Osmo & Bergquist, Bjarne & Vanhatalo, Erik & Kulahci, Murat, 2021. "A taxonomy of railway track maintenance planning and scheduling: A review and research trends," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
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    5. Neves Costa, João & Ambrósio, Jorge & Andrade, António R. & Frey, Daniel, 2023. "Safety assessment using computer experiments and surrogate modeling: Railway vehicle safety and track quality indices," Reliability Engineering and System Safety, Elsevier, vol. 229(C).

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