Zhenkun Huang
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- stochastic dynamics and bifurcation 22
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- Neural Networks Stability and Synchronization 48
- Nonlinear Dynamics and Pattern Formation 15
- Artificial Intelligence top 5%
- Neural Networks and Applications 18
- Modeling and Simulation top 5%
- Applied Mathematics top 5%
- Nonlinear Differential Equations Analysis 4
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- Advanced Memory and Neural Computing 10
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- Mathematical and Theoretical Epidemiology and Ecology Models 8
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- Neural dynamics and brain function 5
- Cited by
- Statistical and Nonlinear PhysicsComputer Networks and CommunicationsArtificial Intelligence
- Partner nations
- ChinaBruneiUnited States
In The Last Decade
Zhenkun Huang
66 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 56
- Statistical and Nonlinear Physics 501
- Computer Networks and Communications 870
- Artificial Intelligence 365
- Modeling and Simulation 47
- Applied Mathematics 78
Countries citing papers authored by Zhenkun Huang
This map shows the geographic impact of Zhenkun Huang'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 Zhenkun Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhenkun Huang more than expected).
Fields of papers citing papers by Zhenkun Huang
This network shows the impact of papers produced by Zhenkun Huang. 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 Zhenkun Huang. The network helps show where Zhenkun Huang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Zhenkun Huang, 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 | 2024 | 3 | |
| 2 | 2023 | 15 | |
| 3 | 2023 | 3 | |
| 4 | 2023 | 1 | |
| 5 | 2023 | 1 | |
| 6 | 2021 | 1 | |
| 7 | 2020 | 1 | |
| 8 | 2019 | 4 | |
| 9 | 2018 | 18 | |
| 10 | 2014 | 22 | |
| 11 | 2013 | 1 | |
| 12 | 2010 | 26 | |
| 13 | 2010 | 5 | |
| 14 | 2009 | 2 | |
| 15 | 2009 | 6 | |
| 16 | 2008 | 20 | |
| 17 | 2007 | 26 | |
| 18 | 2007 | 19 | |
| 19 | 2006 | 32 | |
| 20 | 2005 | 3 |
About Zhenkun Huang
Zhenkun Huang is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications and Modeling and Simulation, having authored 67 papers that have together received 1.1k indexed citations. Recurring topics across this work include Neural Networks Stability and Synchronization (48 papers), stochastic dynamics and bifurcation (22 papers), Neural Networks and Applications (18 papers), Nonlinear Dynamics and Pattern Formation (15 papers), Advanced Memory and Neural Computing (10 papers), Mathematical and Theoretical Epidemiology and Ecology Models (8 papers), Neural dynamics and brain function (5 papers) and Nonlinear Differential Equations Analysis (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (501 citations), Computer Networks and Communications (870 citations) and Artificial Intelligence (365 citations). Zhenkun Huang has collaborated with scholars based in China, Brunei and United States. Frequent co-authors include Yonghui Xia, Xinghua Wang, Jinde Cao, Qiang Xiao, Maoan Han, Sannay Mohamad, Zhigang Zeng, Feng Gao, Chunhua Feng and Xiaobing Nie. Their work appears in journals such as Automatica, IEEE Access and Information Sciences.
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.