Zhenzhen Jin

Orcid: 0000-0001-5003-811X

According to our database1, Zhenzhen Jin authored at least 14 papers between 2022 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Research on flow scheduling of train communication based on time-sensitive network.
Simul. Model. Pract. Theory, January, 2024

Unsupervised intrusion detection for rail transit based on anomaly segmentation.
Signal Image Video Process., 2024

Few-shot fault diagnosis of turnout switch machine based on flexible semi-supervised meta-learning network.
Knowl. Based Syst., 2024

Learning spatial-temporal pairwise and high-order relationships for short-term passenger flow prediction in urban rail transit.
Expert Syst. Appl., 2024

Welding defect detection based on phased array images and two-stage segmentation strategy.
Adv. Eng. Informatics, 2024

2023
Intelligent fault diagnosis and health stage division of bearing based on tensor clustering and feature space denoising.
Appl. Intell., November, 2023

Density-Based Affinity Propagation Tensor Clustering for Intelligent Fault Diagnosis of Train Bogie Bearing.
IEEE Trans. Intell. Transp. Syst., June, 2023

Fault diagnosis of bearing based on refined piecewise composite multivariate multiscale fuzzy entropy.
Digit. Signal Process., March, 2023

Few-shot fault diagnosis of turnout switch machine based on semi-supervised weighted prototypical network.
Knowl. Based Syst., 2023

Blockchain-Empowered Space-Air-Ground Integrated Networks for Remote Internet of Things.
Proceedings of the IEEE/CIC International Conference on Communications in China, 2023

AoI-Aware UAV-Enabled Marine MEC Networks with Integrated Sensing, Computation, and Communication.
Proceedings of the IEEE/CIC International Conference on Communications in China, 2023

2022
Intelligent fault diagnosis of train axle box bearing based on parameter optimization VMD and improved DBN.
Eng. Appl. Artif. Intell., 2022

Fault diagnosis of train rotating parts based on multi-objective VMD optimization and ensemble learning.
Digit. Signal Process., 2022

Cybertwin-Driven Multi-Intelligent Reflecting Surfaces aided Vehicular Edge Computing Leveraged by Deep Reinforcement Learning.
Proceedings of the 96th Vehicular Technology Conference, 2022


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