Li Guo
Orcid: 0000-0002-2707-5833Affiliations:
- Anhui Polytechnic University, School of Electrical Engineering, Wuhu, China
- Hubei Minzu University, Hubei University for Nationalities, Enshi, China
- University of Groningen, Netherlands (2016-2017)
- Sichuan University, School of communication and information system, Chengdu, China (PhD 2013)
According to our database1,
Li Guo
authored at least 14 papers
between 2013 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2024
Prior Knowledge-Augmented Broad Reinforcement Learning Framework for Fault Diagnosis of Heterogeneous Multiagent Systems.
IEEE Trans. Cogn. Dev. Syst., February, 2024
Prognostics of lithium-ion batteries health state based on adaptive mode decomposition and long short-term memory neural network.
Eng. Appl. Artif. Intell., January, 2024
2023
Fault Detection and Diagnosis Using Statistic Feature and Improved Broad Learning for Traction Systems in High-Speed Trains.
IEEE Trans. Artif. Intell., 2023
2021
IEEE Trans. Neural Networks Learn. Syst., 2021
A Cascade Broad Neural Network for Concrete Structural Crack Damage Automated Classification.
IEEE Trans. Ind. Informatics, 2021
A Data-Driven Long Time-Series Electrical Line Trip Fault Prediction Method Using an Improved Stacked-Informer Network.
Sensors, 2021
An accurate and efficient machine fault diagnosis approach using a recurring broad learning model.
J. Syst. Control. Eng., 2021
2020
Automatic crack distress classification from concrete surface images using a novel deep-width network architecture.
Neurocomputing, 2020
2018
J. Control. Sci. Eng., 2018
An Electrical Insulator Defects Detection Method Combined Human Receptive Field Model.
J. Control. Sci. Eng., 2018
2016
J. Sensors, 2016
2014
Super-resolution Reconstruction Algorithm Based on Patch Similarity and Back-projection Modification.
J. Softw., 2014
Multi-scale structural image quality assessment based on two-stage low-level features.
Comput. Electr. Eng., 2014
2013
J. Comput., 2013