Yue Song
- Electrical and Electronic Engineering top 5%
- Control and Systems Engineering top 1%
- Computer Networks and Communications top 5%
- Automotive Engineering top 5%
- Artificial Intelligence top 10%
- Topics
- Optimal Power Flow Distribution (43 papers)Microgrid Control and Optimization (36 papers)Power System Optimization and Stability (31 papers)
- Cited by
- Energy Engineering and Power TechnologyControl and Systems EngineeringElectrical and Electronic Engineering
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Automatic ControlIEEE Transactions on Power Systems
In The Last Decade
Yue Song
106 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 92
- Electrical and Electronic Engineering 1.3k
- Control and Systems Engineering 763
- Computer Networks and Communications 310
- Automotive Engineering 239
- Artificial Intelligence 196
Countries citing papers authored by Yue Song
This map shows the geographic impact of Yue Song'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 Yue Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yue Song more than expected).
Fields of papers citing papers by Yue Song
This network shows the impact of papers produced by Yue Song. 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 Yue Song. The network helps show where Yue Song may publish in the future.
Co-authorship network of co-authors of Yue Song
This figure shows the co-authorship network connecting the top 25 collaborators of Yue Song. A scholar is included among the top collaborators of Yue Song 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 Yue Song. Yue Song 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 | 4 | |
| 4 | 5 | |
| 5 | Ambient Signals based Load Modeling with Combined Gradient-based Optimization and Regression Method. | 2 |
| 6 | 3 | |
| 7 | 30 | |
| 8 | 87 | |
| 9 | 93 | |
| 10 | 21 | |
| 11 | 15 | |
| 12 | 68 | |
| 13 | 168 | |
| 14 | 21 | |
| 15 | 91 | |
| 16 | 2 | |
| 17 | 36 | |
| 18 | 56 | |
| 19 | 9 | |
| 20 | 247 |
About Yue Song
Yue Song is a scholar working on Control and Systems Engineering, Energy Engineering and Power Technology and Electrical and Electronic Engineering, having authored 112 papers that have together received 1.8k indexed citations. Recurring topics across this work include Optimal Power Flow Distribution (43 papers), Microgrid Control and Optimization (36 papers) and Power System Optimization and Stability (31 papers). The work is most often cited by research in Energy Engineering and Power Technology (104 citations), Control and Systems Engineering (763 citations) and Electrical and Electronic Engineering (1.3k citations). Yue Song has collaborated with scholars based in China, Hong Kong and Australia. Frequent co-authors include David J. Hill, Yu Zheng, Murat Demirbaş, Tao Liu, Ke Meng, Suman Chowdhury, Gareth Taylor, Andy Huang, Akshay Kumar Saha and Shunbo Lei. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Automatic Control and IEEE Transactions on Power 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.