Long Yu
Orcid: 0000-0002-5481-8030Affiliations:
- Southwest Jiaotong University, School of Electrical Engineering, Chengdu, China (PhD 2008)
According to our database1,
Long Yu
authored at least 18 papers
between 2018 and 2024.
Collaborative distances:
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Bibliography
2024
Robust deep Gaussian process-based trustworthy fog-haze-caused pollution flashover prediction approach for overhead contact lines.
Reliab. Eng. Syst. Saf., March, 2024
Uncertainty-aware trustworthy weather-driven failure risk predictor for overhead contact lines.
Reliab. Eng. Syst. Saf., February, 2024
2023
A data-driven integrated framework for predictive probabilistic risk analytics of overhead contact lines based on dynamic Bayesian network.
Reliab. Eng. Syst. Saf., July, 2023
A Novel Arcing Detection Model of Pantograph-Catenary for High-Speed Train in Complex Scenes.
IEEE Trans. Instrum. Meas., 2023
Data-driven lightning-related failure risk prediction of overhead contact lines based on Bayesian network with spatiotemporal fragility model.
Reliab. Eng. Syst. Saf., 2023
Weather-Related Failure Risk Prediction of Overhead Contact Lines Based on Deep Gaussian Process.
Proceedings of the 7th International Conference on High Performance Compilation, 2023
2022
IEEE Trans. Intell. Transp. Syst., 2022
Adaptive Deep Learning for High-Speed Railway Catenary Swivel Clevis Defects Detection.
IEEE Trans. Intell. Transp. Syst., 2022
Defect Severity Identification for a Catenary System Based on Deep Semantic Learning.
Sensors, 2022
Predicting wind-caused floater intrusion risk for overhead contact lines based on Bayesian neural network with spatiotemporal correlation analysis.
Reliab. Eng. Syst. Saf., 2022
2021
DefGAN: Defect Detection GANs With Latent Space Pitting for High-Speed Railway Insulator.
IEEE Trans. Instrum. Meas., 2021
Fault Tree Construction Model Based on Association Analysis for Railway Overhead Contact System.
Int. J. Comput. Intell. Syst., 2021
2020
A Robust Pantograph-Catenary Interaction Condition Monitoring Method Based on Deep Convolutional Network.
IEEE Trans. Instrum. Meas., 2020
2019
Deep Architecture for High-Speed Railway Insulator Surface Defect Detection: Denoising Autoencoder With Multitask Learning.
IEEE Trans. Instrum. Meas., 2019
An Efficient Method for High-Speed Railway Dropper Fault Detection Based on Depthwise Separable Convolution.
IEEE Access, 2019
Contact Wire Support Defect Detection Using Deep Bayesian Segmentation Neural Networks and Prior Geometric Knowledge.
IEEE Access, 2019
2018
An Accurate and Efficient Vision Measurement Approach for Railway Catenary Geometry Parameters.
IEEE Trans. Instrum. Meas., 2018