Zili Li

Orcid: 0000-0003-0507-9101

Affiliations:
  • Delft University of Technology, The Netherlands


According to our database1, Zili Li authored at least 12 papers between 2013 and 2023.

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

Timeline

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Bibliography

2023
Theoretical Framework for a Succinct Empirical Mode Decomposition.
IEEE Signal Process. Lett., 2023

2022
A multiple spiking neural network architecture based on fuzzy intervals for anomaly detection: a case study of rail defects.
Proceedings of the IEEE International Conference on Fuzzy Systems, 2022

2018
An Integrated Approach for Characterizing the Dynamic Behavior of the Wheel-Rail Interaction at Crossings.
IEEE Trans. Instrum. Meas., 2018

A Condition-Based Maintenance Methodology for Rails in Regional Railway Networks Using Evolutionary Multiobjective Optimization.
Proceedings of the 2018 IEEE Congress on Evolutionary Computation, 2018

2017
Evaluating Degradation at Railway Crossings Using Axle Box Acceleration Measurements.
Sensors, 2017

2015
Improvements in Axle Box Acceleration Measurements for the Detection of Light Squats in Railway Infrastructure.
IEEE Trans. Ind. Electron., 2015

Model Predictive Control for Maintenance Operations Planning of Railway Infrastructures.
Proceedings of the Computational Logistics - 6th International Conference, 2015

2014
Automatic Detection of Squats in Railway Infrastructure.
IEEE Trans. Intell. Transp. Syst., 2014

Evaluating Classification Performance with only Positive and Unlabeled Samples.
Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2014

Axle box acceleration for health monitoring of insulated joints: A case study in the Netherlands.
Proceedings of the 17th International IEEE Conference on Intelligent Transportation Systems, 2014

Facilitating maintenance decisions on the Dutch railways using big data: The ABA case study.
Proceedings of the 2014 IEEE International Conference on Big Data (IEEE BigData 2014), 2014

2013
Monitoring the railway infrastructure: Detection of surface defects using wavelets.
Proceedings of the 16th International IEEE Conference on Intelligent Transportation Systems, 2013


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