Jun Zhang
Impact in
- Computational Theory and Mathematics top 0.01%
- Advanced Multi-Objective Optimization Algorithms
- Artificial Intelligence top 0.01%
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
Papers in
-
- Metaheuristic Optimization Algorithms Research 461
- Evolutionary Algorithms and Applications 309
- Neural Networks and Applications 48
-
- Advanced Multi-Objective Optimization Algorithms 293
- Co-authors
- Zhi‐Hui Zhan (190 shared papers)Yun Li (41 shared papers)Wei–Neng Chen (126 shared papers)Henry Shu-Hung Chung (32 shared papers)Yue‐Jiao Gong (85 shared papers)Yuhui Shi (15 shared papers)Sam Kwong (48 shared papers)Bing Xue (66 shared papers)
- Journals
- IEEE Transactions on Evolutionary Computation (74 papers)IEEE Transactions on Cybernetics (69 papers)IEEE Transactions on Systems Man and Cybernetics Systems (18 papers)IEEE Transactions on Intelligent Transportation Systems (18 papers)Applied Soft Computing (18 papers)
- Partner nations
- ChinaUnited StatesNew Zealand
In The Last Decade
Jun Zhang
2.5k papers receiving 54.8k citations
Jun Zhang's Hit Papers
Peers
Comparison fields: 5 of 240
- Computational Theory and Mathematics 10.0k
- Artificial Intelligence 17.8k
- Industrial and Manufacturing Engineering 3.2k
- Computer Vision and Pattern Recognition 4.0k
- Computer Networks and Communications 4.4k
Countries citing papers authored by Jun Zhang
This map shows the geographic impact of Jun Zhang'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 Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Zhang more than expected).
Fields of papers citing papers by Jun Zhang
This network shows the impact of papers produced by Jun Zhang. 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 Zhang. The network helps show where Jun Zhang may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Zhang, 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 2.7k papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Adaptive Particle Swarm Optimization Hit paper breakdown → | 2009 | 1550 |
| 2 | Orthogonal Learning Particle Swarm Optimization Hit paper breakdown → | 2010 | 613 |
| 3 | ABCluster: the artificial bee colony algorithm for cluster global optimization Hit paper breakdown → | 2015 | 559 |
| 4 | A hybrid particle swarm optimization–back-propagation algorithm for feedforward neural network training Hit paper breakdown → | 2006 | 549 |
| 5 | Dynamical properties of hybrid automata Hit paper breakdown → | 2003 | 546 |
| 6 | Particle Swarm Optimization With an Aging Leader and Challengers Hit paper breakdown → | 2012 | 504 |
| 7 | Genetic Learning Particle Swarm Optimization Hit paper breakdown → | 2015 | 444 |
| 8 | Cloud Computing Resource Scheduling and a Survey of Its Evolutionary Approaches Hit paper breakdown → | 2015 | 361 |
| 9 | 2007 | 335 | |
| 10 | An Energy Efficient Ant Colony System for Virtual Machine Placement in Cloud Computing Hit paper breakdown → | 2016 | 320 |
| 11 | A Novel Set-Based Particle Swarm Optimization Method for Discrete Optimization Problems Hit paper breakdown → | 2009 | 319 |
| 12 | The challenge and prospect of mRNA therapeutics landscape Hit paper breakdown → | 2020 | 310 |
| 13 | Differential evolution for filter feature selection based on information theory and feature ranking Hit paper breakdown → | 2017 | 296 |
| 14 | Fuzzy-Based Pareto Optimality for Many-Objective Evolutionary Algorithms Hit paper breakdown → | 2013 | 288 |
| 15 | Self-Adaptive Particle Swarm Optimization for Large-Scale Feature Selection in Classification Hit paper breakdown → | 2019 | 280 |
| 16 | 2012 | 276 | |
| 17 | 2008 | 275 | |
| 18 | Distributed evolutionary algorithms and their models: A survey of the state-of-the-art Hit paper breakdown → | 2015 | 272 |
| 19 | A survey on evolutionary computation for complex continuous optimization Hit paper breakdown → | 2021 | 271 |
| 20 | 2018 | 270 |
About Jun Zhang
Jun Zhang is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Electrical and Electronic Engineering, Molecular Biology and Biomedical Engineering, having authored 2.7k papers that have together received 56.5k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (461 papers), Evolutionary Algorithms and Applications (309 papers), Advanced Multi-Objective Optimization Algorithms (293 papers), Vehicle Routing Optimization Methods (75 papers), Complex Network Analysis Techniques (55 papers), Robotic Path Planning Algorithms (51 papers), Neural Networks and Applications (48 papers) and Optical Coherence Tomography Applications (47 papers). The work is most often cited by research in Computational Theory and Mathematics (10.0k citations), Artificial Intelligence (17.8k citations), Industrial and Manufacturing Engineering (3.2k citations), Computer Vision and Pattern Recognition (4.0k citations) and Computer Networks and Communications (4.4k citations). Jun Zhang has collaborated with scholars based in China, United States and New Zealand. Frequent co-authors include Zhi‐Hui Zhan, Yun Li, Wei–Neng Chen, Henry Shu-Hung Chung, Yue‐Jiao Gong, Yuhui Shi, Sam Kwong, Bing Xue, Ying Lin and Tianlong Gu. Their work appears in journals such as IEEE Transactions on Evolutionary Computation, IEEE Transactions on Cybernetics, IEEE Transactions on Systems Man and Cybernetics Systems, IEEE Transactions on Intelligent Transportation Systems and Applied Soft Computing.
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.