Hangjun Zhou
Impact in
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- Multi-Criteria Decision Making
Papers in
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- Advanced Decision-Making Techniques 6
- Cloud Computing and Resource Management 6
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- Multi-Criteria Decision Making 12
- Co-authors
- Sha Fu (21 shared papers)Guang Sun (3 shared papers)Jieyu Zhou (1 shared paper)Xingxing Zhou (1 shared paper)Jing Liu (1 shared paper)Linli Wang (1 shared paper)Ying Gao (1 shared paper)Wangdong Jiang (1 shared paper)
- Journals
- IEEE Access (3 papers)Scientific Reports (2 papers)Journal of Applied Sciences (2 papers)Computers, materials & continua/Computers, materials & continua (Print) (2 papers)ACM SIGMETRICS Performance Evaluation Review (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Hangjun Zhou
30 papers receiving 280 citations
Peers
Comparison fields: 5 of 69
- Management Science and Operations Research 99
- Management Information Systems 32
- Accounting 39
- Statistics and Probability 27
- Artificial Intelligence 99
Countries citing papers authored by Hangjun Zhou
This map shows the geographic impact of Hangjun Zhou'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 Hangjun Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hangjun Zhou more than expected).
Fields of papers citing papers by Hangjun Zhou
This network shows the impact of papers produced by Hangjun Zhou. 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 Hangjun Zhou. The network helps show where Hangjun Zhou may publish in the future.
Co-authors
The 25 scholars most cited alongside Hangjun Zhou, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 67 | |
| 2 | 2021 | 58 | |
| 3 | 2020 | 32 | |
| 4 | 2016 | 24 | |
| 5 | 2022 | 16 | |
| 6 | 2011 | 16 | |
| 7 | 2021 | 16 | |
| 8 | 2022 | 12 | |
| 9 | 2021 | 11 | |
| 10 | 2020 | 9 | |
| 11 | 2018 | 8 | |
| 12 | 2018 | 6 | |
| 13 | 2011 | 4 | |
| 14 | 2010 | 4 | |
| 15 | 2020 | 4 | |
| 16 | 2014 | 2 | |
| 17 | 2010 | 2 | |
| 18 | 2009 | 2 | |
| 19 | 2014 | 2 | |
| 20 | 2014 | 2 |
About Hangjun Zhou
Hangjun Zhou is a scholar working on Information Systems, Management Science and Operations Research, Computer Networks and Communications, Artificial Intelligence and Ecological Modeling, having authored 34 papers that have together received 307 indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (12 papers), Advanced Decision-Making Techniques (6 papers), Cloud Computing and Resource Management (6 papers), Peer-to-Peer Network Technologies (5 papers), Imbalanced Data Classification Techniques (4 papers), Caching and Content Delivery (3 papers), Evaluation Methods in Various Fields (3 papers) and Evaluation and Optimization Models (2 papers). The work is most often cited by research in Management Science and Operations Research (99 citations), Management Information Systems (32 citations), Accounting (39 citations), Statistics and Probability (27 citations) and Artificial Intelligence (99 citations). Hangjun Zhou has collaborated with scholars based in China and United States. Frequent co-authors include Sha Fu, Guang Sun, Jieyu Zhou, Xingxing Zhou, Jing Liu, Linli Wang, Ying Gao, Wangdong Jiang, Guang Sun and Shuting Hu. Their work appears in journals such as IEEE Access, Scientific Reports, Journal of Applied Sciences, Computers, materials & continua/Computers, materials & continua (Print) and ACM SIGMETRICS Performance Evaluation Review.
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.