Anqi Pan
Impact in
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- Advanced Multi-Objective Optimization Algorithms
- Artificial Intelligence top 10%
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
Papers in
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- Metaheuristic Optimization Algorithms Research 17
- Evolutionary Algorithms and Applications 7
- Reinforcement Learning in Robotics 2
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- Advanced Multi-Objective Optimization Algorithms 16
- Co-authors
- Hongliang Ren (5 shared papers)Tianliang Li (3 shared papers)Bo Shen (10 shared papers)Dawei Li (1 shared paper)Jiankai Xue (5 shared papers)Qidi Wu (4 shared papers)Weian Guo (4 shared papers)Lei Wang (2 shared papers)
In The Last Decade
Anqi Pan
38 papers receiving 419 citations
Peers
Comparison fields: 5 of 88
- Computational Theory and Mathematics 79
- Artificial Intelligence 117
- Control and Systems Engineering 70
- Environmental Engineering 36
- Biomedical Engineering 103
Countries citing papers authored by Anqi Pan
This map shows the geographic impact of Anqi Pan'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 Anqi Pan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anqi Pan more than expected).
Fields of papers citing papers by Anqi Pan
This network shows the impact of papers produced by Anqi Pan. 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 Anqi Pan. The network helps show where Anqi Pan may publish in the future.
Co-authors
The 25 scholars most cited alongside Anqi Pan, 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 43 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 60 | |
| 2 | 2022 | 53 | |
| 3 | 2020 | 41 | |
| 4 | 2018 | 25 | |
| 5 | 2020 | 20 | |
| 6 | 2019 | 17 | |
| 7 | 2023 | 16 | |
| 8 | 2022 | 14 | |
| 9 | 2014 | 14 | |
| 10 | 2021 | 14 | |
| 11 | 2019 | 14 | |
| 12 | 2022 | 14 | |
| 13 | 2023 | 13 | |
| 14 | 2023 | 10 | |
| 15 | 2024 | 10 | |
| 16 | 2016 | 8 | |
| 17 | 2022 | 8 | |
| 18 | 2023 | 8 | |
| 19 | 2022 | 8 | |
| 20 | 2018 | 7 |
About Anqi Pan
Anqi Pan is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Control and Systems Engineering, Electrical and Electronic Engineering and Computer Networks and Communications, having authored 43 papers that have together received 423 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (17 papers), Advanced Multi-Objective Optimization Algorithms (16 papers), Evolutionary Algorithms and Applications (7 papers), Advanced Control Systems Optimization (2 papers), Reinforcement Learning in Robotics (2 papers), Topology Optimization in Engineering (2 papers), Advanced Fiber Optic Sensors (2 papers) and Energy Efficient Wireless Sensor Networks (2 papers). The work is most often cited by research in Computational Theory and Mathematics (79 citations), Artificial Intelligence (117 citations), Control and Systems Engineering (70 citations), Environmental Engineering (36 citations) and Biomedical Engineering (103 citations). Anqi Pan has collaborated with scholars based in China, Singapore and Australia. Frequent co-authors include Hongliang Ren, Tianliang Li, Bo Shen, Dawei Li, Jiankai Xue, Qidi Wu, Weian Guo, Lei Wang, Xue Feng and Wenjun Xu. Their work appears in journals such as Applied Soft Computing, Information Sciences, Swarm and Evolutionary Computation, Engineering Applications of Artificial Intelligence and Expert Systems with Applications.
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.