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February 2, 2025Neurocomputers

Application of hybrid neural networks to predict changes in the technical condition of a railway track

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Authors

MLM.A. LudagovskayaЕЛЕва Денисовна Ларионова

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Implication

Application of hybrid neural networks predicts the technical condition of railway tracks, suggesting integration with automated systems.

Key Points

  • Hybrid neural networks effectively predict the technical condition of railway tracks, facilitating maintenance planning.
  • The study employs LSTM and CNN models to analyze diagnostic data from sensors on track measuring wagons.
  • Analysis of large datasets enhances the accuracy of predictions regarding changes in track condition.
  • Integrating neural network models may streamline automated monitoring and diagnostics in railway transport systems.

Cite This Study

Ludagovskaya et al. (2025) studied this question.

synapsesocial.com/papers/68af6bf77567bf4f94fe95f9https://doi.org/10.18127/j19998554-202502-07
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