Enhancing the Effectiveness of Neural Networks in Predicting Railway Track Degradation
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-39619-9_48
Reference30 articles.
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2. Soleimanmeigouni I, Ahmadi A, Kumar U (2018) Track geometry degradation and maintenance modelling: a review. Proc Inst Mech Eng Part F J Rail Rapid Transit. https://doi.org/10.1177/0954409716657849
3. Hewamalage H, Bergmeir C, Bandara K (2021) Recurrent neural networks for time series forecasting: current status and future directions. Int J Forecast 37. https://doi.org/10.1016/j.ijforecast.2020.06.008
4. Guler H (2014) Prediction of railway track geometry deterioration using artificial neural networks: a case study for Turkish state railways. Struct Infrastruct Eng 10. https://doi.org/10.1080/15732479.2012.757791
5. Falamarzi A, Moridpour S, Nazem M (2019) A review of rail track degradation prediction models. Aust J Civ Eng. https://doi.org/10.1080/14488353.2019.1667710
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