Sheng‐Ming Yang

1.5k citations
71 papers · 1.2k · h-index 21

Impact in

Papers in

Sheng‐Ming Yang

71 papers receiving 1.2k citations

Peers

Sheng‐Ming Yang
Comparison fields: 5 of 54
  • Control and Systems Engineering 796
  • Electrical and Electronic Engineering 962
  • Mechanical Engineering 379
  • Electronic, Optical and Magnetic Materials 118
  • Automotive Engineering 35
Replace Takaaki OIWA with:
Takaaki OIWA Japan
J. Cros Canada
Dae‐Hyun Koo South Korea
Han-Wook Cho South Korea
E. Masada Japan
Cheng-Tsung Liu Taiwan
Yon‐Do Chun South Korea
Li Yu China
Seok–Myeong Jang South Korea
Marcel Jufer Switzerland
Sheng‐Ming Yang relative to Takaaki OIWA Japan Takaaki OIWA's profile →
Citations per field
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Citations per year

Countries citing papers authored by Sheng‐Ming Yang

Since Specialization
Citations

This map shows the geographic impact of Sheng‐Ming Yang'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 Sheng‐Ming Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sheng‐Ming Yang more than expected).

Fields of papers citing papers by Sheng‐Ming Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sheng‐Ming Yang. 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 Sheng‐Ming Yang. The network helps show where Sheng‐Ming Yang may publish in the future.

Co-authors

The 22 scholars most cited alongside Sheng‐Ming Yang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sheng‐Ming Yang Line = papers co-authored together Sheng‐Ming Yang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201594
2 200076
3 200267
4 200967
5 200358
6 200755
7 200751
8 201644
9 200743
10 200543
11 199241
12 201038
13 201433
14 201232
15 200432
16 200931
17 200530
18 200327
19 200226
20 198823

About Sheng‐Ming Yang

Sheng‐Ming Yang is a scholar working on Electrical and Electronic Engineering, Control and Systems Engineering, Mechanical Engineering, Electronic, Optical and Magnetic Materials and Biomedical Engineering, having authored 71 papers that have together received 1.2k indexed citations. Recurring topics across this work include Electric Motor Design and Analysis (51 papers), Sensorless Control of Electric Motors (34 papers), Magnetic Bearings and Levitation Dynamics (32 papers), Multilevel Inverters and Converters (17 papers), Magnetic Properties and Applications (11 papers), Iterative Learning Control Systems (10 papers), Control Systems in Engineering (8 papers) and Characterization and Applications of Magnetic Nanoparticles (5 papers). The work is most often cited by research in Control and Systems Engineering (796 citations), Electrical and Electronic Engineering (962 citations), Mechanical Engineering (379 citations), Electronic, Optical and Magnetic Materials (118 citations) and Automotive Engineering (35 citations). Sheng‐Ming Yang has collaborated with scholars based in Taiwan and United States. Frequent co-authors include R. D. Lorenz, Ming‐Shi Huang, Shih-Chin Yang, Jianyu Chen, Jing Hu, Hong-Quan Nguyen, Ming‐Tang Chen, Giovanni Vannucci, Jiahao Zhang and Chun‐Cheng Lin. Their work appears in journals such as IEEE Transactions on Industrial Electronics, IEEE Access, IEEE Transactions on Industry Applications, IEEE Transactions on Magnetics and IEEE Transactions on Power Electronics.

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.

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