Estimating the occurrence of broken rails in commuter railroads with machine learning algorithms
Di Kang,
Junyan Dai,
Xiang Liu
et al.
Abstract:Broken rail prevention is critical for ensuring track infrastructure safety. With the increasing availability of rail data, the opportunity for data-driven analyses emerges as a promising avenue for enhancing railroad safety. While previous research has predominantly concentrated on predicting broken rails within the context of freight railroads, the attention afforded to commuter railroads has been limited. To address this research gap, this paper presents an analytical modeling framework based on machine lea… Show more
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