Qing-Hua Ling
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 5%
- Computational Theory and Mathematics top 2%
- Electrical and Electronic Engineering
- Control and Systems Engineering top 10%
- Co-authors
- Fei HanHenry HanDe-Shuang HuangJing JiangBenyue SuArfan Ali NagraJie WangYuqing Song
- Topics
- Metaheuristic Optimization Algorithms Research (31 papers)Advanced Multi-Objective Optimization Algorithms (20 papers)Machine Learning and ELM (14 papers)
- Cited by
- Artificial IntelligenceComputational Theory and MathematicsComputer Vision and Pattern Recognition
- Partner nations
- ChinaUnited StatesGhana
In The Last Decade
Qing-Hua Ling
42 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 103
- Artificial Intelligence 686
- Computer Vision and Pattern Recognition 244
- Computational Theory and Mathematics 228
- Electrical and Electronic Engineering 141
- Control and Systems Engineering 113
Countries citing papers authored by Qing-Hua Ling
This map shows the geographic impact of Qing-Hua Ling'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 Qing-Hua Ling with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qing-Hua Ling more than expected).
Fields of papers citing papers by Qing-Hua Ling
This network shows the impact of papers produced by Qing-Hua Ling. 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 Qing-Hua Ling. The network helps show where Qing-Hua Ling may publish in the future.
Co-authorship network of co-authors of Qing-Hua Ling
This figure shows the co-authorship network connecting the top 25 collaborators of Qing-Hua Ling. A scholar is included among the top collaborators of Qing-Hua Ling based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Qing-Hua Ling. Qing-Hua Ling is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 5 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 0 | |
| 9 | 0 | |
| 10 | 13 | |
| 11 | 24 | |
| 12 | 1 | |
| 13 | 129 | |
| 14 | 13 | |
| 15 | 27 | |
| 16 | 55 | |
| 17 | 14 | |
| 18 | 7 | |
| 19 | 21 | |
| 20 | 2 |
About Qing-Hua Ling
Qing-Hua Ling is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition, having authored 51 papers that have together received 1.1k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (31 papers), Advanced Multi-Objective Optimization Algorithms (20 papers) and Machine Learning and ELM (14 papers). The work is most often cited by research in Artificial Intelligence (686 citations), Computational Theory and Mathematics (228 citations) and Computer Vision and Pattern Recognition (244 citations). Qing-Hua Ling has collaborated with scholars based in China, United States and Ghana. Frequent co-authors include Fei Han, Henry Han, De-Shuang Huang, Jing Jiang, Fei Han, Benyue Su, Arfan Ali Nagra, Jie Wang, Yuqing Song and Jianming Zhang. Their work appears in journals such as PLoS ONE, Expert Systems with Applications and IEEE Access.
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.