Hao Ren
Orcid: 0000-0001-8471-9132Affiliations:
- Peng Cheng Laboratory, Department of Strategic and Advanced Interdisciplinary Research, Shenzhen, China
- Huawei Technologies Co., Ltd., Edge Innovation Lab, Shenzhen, China (2019-2020)
- Chongqing University, Department of control science and control engineering, China (PhD 2019)
According to our database1,
Hao Ren
authored at least 12 papers
between 2018 and 2024.
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Bibliography
2024
Knowledge-Data-Based Synchronization States Analysis for Process Monitoring and Its Application to Hydrometallurgical Zinc Purification Process.
IEEE Trans. Ind. Informatics, January, 2024
2023
Association Hierarchical Representation Learning for Plant-Wide Process Monitoring by Using Multilevel Knowledge Graph.
IEEE Trans. Artif. Intell., 2023
Proceedings of the 29th IEEE International Conference on Parallel and Distributed Systems, 2023
An Ontology for Industrial Intelligent Model Library and Its Distributed Computing Application.
Proceedings of the Neural Information Processing - 30th International Conference, 2023
2022
Spatial-temporal associations representation and application for process monitoring using graph convolution neural network.
CoRR, 2022
2021
An Industrial Multilevel Knowledge Graph-Based Local-Global Monitoring for Plant-Wide Processes.
IEEE Trans. Instrum. Meas., 2021
Improved sparse representation based on local preserving projection for the fault diagnosis of multivariable system.
Sci. China Inf. Sci., 2021
A fault detection method based on stacking the SAE-SRBM for nonstationary and stationary hybrid processes.
Int. J. Appl. Math. Comput. Sci., 2021
2020
A Fault Diagnosis Methodology Based on Non-Stationary Monitoring Signals by Extracting Features With Unknown Probability Distribution.
IEEE Access, 2020
2019
The input pattern problem on deep learning applied to signal analysis and processing to achieve fault diagnosis.
Sci. China Inf. Sci., 2019
2018
Trans. Inst. Meas. Control, 2018
A novel adaptive fault detection methodology for complex system using deep belief networks and multiple models: A case study on cryogenic propellant loading system.
Neurocomputing, 2018