M.-S. Chen
- Electrical and Electronic Engineering top 5%
- Control and Systems Engineering top 2%
- Artificial Intelligence top 10%
- Safety, Risk, Reliability and Quality top 5%
- Management Science and Operations Research top 10%
- Co-authors
- W. CharytoniukTomoyasu InoueM.T. ManryP. Van OlindaR.R. ShoultsChih-Chien LiangRenli YangFei Chen
- Topics
- Neural Networks and Applications (7 papers)Fuzzy Logic and Control Systems (6 papers)Optimal Power Flow Distribution (5 papers)
- Cited by
- Control and Systems EngineeringElectrical and Electronic EngineeringSafety, Risk, Reliability and Quality
- Partner nations
- United StatesIndiaChina
In The Last Decade
M.-S. Chen
12 papers receiving 930 citations
Hit Papers
Peers
Comparison fields: 5 of 60
- Electrical and Electronic Engineering 900
- Control and Systems Engineering 559
- Artificial Intelligence 131
- Safety, Risk, Reliability and Quality 84
- Management Science and Operations Research 76
Countries citing papers authored by M.-S. Chen
This map shows the geographic impact of M.-S. Chen'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 M.-S. Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M.-S. Chen more than expected).
Fields of papers citing papers by M.-S. Chen
This network shows the impact of papers produced by M.-S. Chen. 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 M.-S. Chen. The network helps show where M.-S. Chen may publish in the future.
Co-authorship network of co-authors of M.-S. Chen
This figure shows the co-authorship network connecting the top 25 collaborators of M.-S. Chen. A scholar is included among the top collaborators of M.-S. Chen 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 M.-S. Chen. M.-S. Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 6 | |
| 5 | 4 | |
| 6 | 208 | |
| 7 | 40 | |
| 8 | 17 | |
| 9 | 62 | |
| 10 | 2 | |
| 11 | 4 | |
| 12 | Distribution system power flow analysis-a rigid approachbreakdown → | 380 |
| 13 | 236 | |
| 14 | 26 | |
| 15 | 36 |
About M.-S. Chen
M.-S. Chen is a scholar working on Signal Processing, Artificial Intelligence and Control and Systems Engineering, having authored 15 papers that have together received 1.0k indexed citations. Recurring topics across this work include Neural Networks and Applications (7 papers), Fuzzy Logic and Control Systems (6 papers) and Optimal Power Flow Distribution (5 papers). The work is most often cited by research in Control and Systems Engineering (559 citations), Electrical and Electronic Engineering (900 citations) and Safety, Risk, Reliability and Quality (84 citations). M.-S. Chen has collaborated with scholars based in United States, India and China. Frequent co-authors include W. Charytoniuk, Tomoyasu Inoue, M.T. Manry, P. Van Olinda, R.R. Shoults, Chih-Chien Liang, Renli Yang and Fei Chen. Their work appears in journals such as IEEE Transactions on Power Systems, IEEE Transactions on Power Delivery and Energies.
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.