Cargando…
Prognostics of unsupported railway sleepers and their severity diagnostics using machine learning
Railway sleepers are safety–critical components of a railway structure. They support ballasted track superstructure and are a critical factor in track geometry and track components’ deterioration. Unsupported sleepers are a common issue incurred after tracks have been utilized. When unsupported slee...
Autores principales: | Sresakoolchai, Jessada, Kaewunruen, Sakdirat |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9001734/ https://www.ncbi.nlm.nih.gov/pubmed/35411031 http://dx.doi.org/10.1038/s41598-022-10062-w |
Ejemplares similares
-
Automated machine learning recognition to diagnose flood resilience of railway switches and crossings
por: Sresakoolchai, Jessada, et al.
Publicado: (2023) -
Railway infrastructure maintenance efficiency improvement using deep reinforcement learning integrated with digital twin based on track geometry and component defects
por: Sresakoolchai, Jessada, et al.
Publicado: (2023) -
Digital twins for managing railway maintenance and resilience
por: Kaewunruen, Sakdirat, et al.
Publicado: (2021) -
Prediction of Healing Performance of Autogenous Healing Concrete Using Machine Learning
por: Huang, Xu, et al.
Publicado: (2021) -
Track Geometry Prediction Using Three-Dimensional Recurrent Neural Network-Based Models Cross-Functionally Co-Simulated with BIM
por: Sresakoolchai, Jessada, et al.
Publicado: (2022)