Jun Zhan
Impact in
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- Multi-Criteria Decision Making
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- Risk and Safety Analysis
Papers in
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- Machine Fault Diagnosis Techniques 6
- Fault Detection and Control Systems 2
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- Anomaly Detection Techniques and Applications 2
- Target Tracking and Data Fusion in Sensor Networks 2
- Co-authors
- Wen Jiang (4 shared papers)Deyun Zhou (2 shared papers)Boya Wei (2 shared papers)Yu Luo (1 shared paper)Xin Li (1 shared paper)Chunhe Xie (1 shared paper)Xiandong Ma (3 shared papers)Chengkun Wu (5 shared papers)
- Journals
- Applied Intelligence (1 paper)IEEE Sensors Journal (1 paper)Information Sciences (1 paper)Mechanical Systems and Signal Processing (1 paper)Computers & Industrial Engineering (1 paper)
- Partner nations
- ChinaUnited Kingdom
In The Last Decade
Jun Zhan
16 papers receiving 488 citations
Peers
Comparison fields: 5 of 80
- Management Science and Operations Research 174
- Statistics, Probability and Uncertainty 51
- Control and Systems Engineering 132
- Artificial Intelligence 180
- Computational Theory and Mathematics 85
Countries citing papers authored by Jun Zhan
This map shows the geographic impact of Jun Zhan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jun Zhan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Zhan more than expected).
Fields of papers citing papers by Jun Zhan
This network shows the impact of papers produced by Jun Zhan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jun Zhan. The network helps show where Jun Zhan may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Zhan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 108 | |
| 2 | 2016 | 72 | |
| 3 | 2015 | 69 | |
| 4 | 2016 | 58 | |
| 5 | 2022 | 46 | |
| 6 | 2016 | 44 | |
| 7 | 2022 | 25 | |
| 8 | 2020 | 23 | |
| 9 | 2018 | 21 | |
| 10 | 2021 | 9 | |
| 11 | 2024 | 4 | |
| 12 | 2024 | 4 | |
| 13 | 2024 | 4 | |
| 14 | 2021 | 4 | |
| 15 | 2020 | 3 | |
| 16 | 2021 | 1 | |
| 17 | 2019 | 0 | |
| 18 | 2022 | 0 | |
| 19 | Q-FUZZY DOT SUBALGEBRAS OF BCK/BCI-ALGEBRAS | 2003 | 0 |
About Jun Zhan
Jun Zhan is a scholar working on Control and Systems Engineering, Artificial Intelligence, Management Science and Operations Research, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 19 papers that have together received 495 indexed citations. Recurring topics across this work include Machine Fault Diagnosis Techniques (6 papers), Multi-Criteria Decision Making (4 papers), Anomaly Detection Techniques and Applications (2 papers), Network Security and Intrusion Detection (2 papers), Rough Sets and Fuzzy Logic (2 papers), Target Tracking and Data Fusion in Sensor Networks (2 papers), Fault Detection and Control Systems (2 papers) and Military Defense Systems Analysis (1 paper). The work is most often cited by research in Management Science and Operations Research (174 citations), Statistics, Probability and Uncertainty (51 citations), Control and Systems Engineering (132 citations), Artificial Intelligence (180 citations) and Computational Theory and Mathematics (85 citations). Jun Zhan has collaborated with scholars based in China and United Kingdom. Frequent co-authors include Wen Jiang, Deyun Zhou, Boya Wei, Yu Luo, Xin Li, Chunhe Xie, Xiandong Ma, Chengkun Wu, Shilin Wang and Yongchuan Tang. Their work appears in journals such as Applied Intelligence, IEEE Sensors Journal, Information Sciences, Mechanical Systems and Signal Processing and Computers & Industrial Engineering.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.