Fault Early Warning Model for High-Speed Railway Train Based on Feature Contribution and Causal Inference

Fault Early Warning Model for High-Speed Railway Train Based on Feature Contribution and Causal Inference

The demands for model accuracy and computing efficiency in fault warning scenarios are increasing as high-speed railway train technology continues to advance. The black box model is difficult to interpret, making it impossible for this technology to be widely adopted in the railway industry, which h...

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Bibliographic Details
Main Authors: Dian Liu, Yong Qin, Yiying Zhao, Weijun Yang, Haijun Hu, Ning Yang, Bing Liu
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Sensors
Subjects:
causal inference
SHAP
interpretability
data-driven
fault warning
Online Access:https://www.mdpi.com/1424-8220/22/23/9184

Internet

https://www.mdpi.com/1424-8220/22/23/9184

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