Gang Leng
- Artificial Intelligence top 5%
- Control and Systems Engineering top 5%
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition top 10%
- Management Science and Operations Research top 10%
- Co-authors
- T.M. McGinnityGirijesh PrasadJohn KeaneXiao‐Jun ZengYongjie ZhaiHuina MaoMichael EverettPlamen Angelov
- Topics
- Fuzzy Logic and Control Systems (9 papers)Neural Networks and Applications (8 papers)Advanced Algorithms and Applications (2 papers)
- Partner nations
- United KingdomChinaUnited States
In The Last Decade
Gang Leng
14 papers receiving 599 citations
Peers
Comparison fields: 5 of 67
- Artificial Intelligence 431
- Control and Systems Engineering 180
- Electrical and Electronic Engineering 105
- Computer Vision and Pattern Recognition 77
- Management Science and Operations Research 75
Countries citing papers authored by Gang Leng
This map shows the geographic impact of Gang Leng'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 Gang Leng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gang Leng more than expected).
Fields of papers citing papers by Gang Leng
This network shows the impact of papers produced by Gang Leng. 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 Gang Leng. The network helps show where Gang Leng may publish in the future.
Co-authorship network of co-authors of Gang Leng
This figure shows the co-authorship network connecting the top 25 collaborators of Gang Leng. A scholar is included among the top collaborators of Gang Leng 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 Gang Leng. Gang Leng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Online Sliding Window Based Self-Organising Fuzzy Neural Network for Cognitive Reasoning | 4 |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 8 | |
| 5 | 16 | |
| 6 | 5 | |
| 7 | 61 | |
| 8 | 23 | |
| 9 | A Passive Approach to Autonomous Collision Detection and Avoidance in Uninhabited Aerial Systems. | 12 |
| 10 | 20 | |
| 11 | 4 | |
| 12 | 139 | |
| 13 | 133 | |
| 14 | 192 |
About Gang Leng
Gang Leng is a scholar working on Energy Engineering and Power Technology, Artificial Intelligence and Control and Systems Engineering, having authored 14 papers that have together received 621 indexed citations. Recurring topics across this work include Fuzzy Logic and Control Systems (9 papers), Neural Networks and Applications (8 papers) and Advanced Algorithms and Applications (2 papers). The work is most often cited by research in Artificial Intelligence (431 citations), Control and Systems Engineering (180 citations) and Statistics and Probability (55 citations). Gang Leng has collaborated with scholars based in United Kingdom, China and United States. Frequent co-authors include T.M. McGinnity, Girijesh Prasad, John Keane, Xiao‐Jun Zeng, Yongjie Zhai, Huina Mao, Michael Everett, Plamen Angelov, Anjan Kumar Ray and Liam Maguire. Their work appears in journals such as IEEE Transactions on Power Systems, IEEE Transactions on Fuzzy Systems and Fuzzy Sets and Systems.
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.