Yu Kang

8.1k citations
349 papers · 6.1k · h-index 43

Impact in

Papers in

Yu Kang

318 papers receiving 5.9k citations

Peers

Yu Kang
Comparison fields: 5 of 171
  • Control and Systems Engineering 2.5k
  • Computer Networks and Communications 1.9k
  • Geochemistry and Petrology 272
  • Automotive Engineering 477
  • Computer Vision and Pattern Recognition 545
Replace Jie Liu with:
Jie Liu China
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Dan Wang China
Wenyuan Li China
Peng Zeng China
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Shaoping Wang China
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Citations per field
00.5×5.6×
Jie Liu · 1×
Citations per year

Countries citing papers authored by Yu Kang

Since Specialization
Citations

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

Fields of papers citing papers by Yu Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yu Kang. 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 Yu Kang. The network helps show where Yu Kang may publish in the future.

Co-authors

The 25 scholars most cited alongside Yu Kang, 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 Yu Kang Line = papers co-authored together Yu Kang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 349 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017204
2 2018204
3 2019161
4 2011161
5 2017146
6 2010138
7 2012133
8 2016124
9 2018117
10 2012111
11 2014108
12 2019103
13 2015103
14 201886
15 201885
16 201985
17 201481
18 201780
19 202078
20 201874

About Yu Kang

Yu Kang is a scholar working on Control and Systems Engineering, Computer Networks and Communications, Artificial Intelligence, Electrical and Electronic Engineering and Automotive Engineering, having authored 349 papers that have together received 6.1k indexed citations. Recurring topics across this work include Stability and Control of Uncertain Systems (52 papers), Distributed Control Multi-Agent Systems (48 papers), Neural Networks Stability and Synchronization (43 papers), Adaptive Control of Nonlinear Systems (41 papers), Advanced Control Systems Optimization (36 papers), Air Quality Monitoring and Forecasting (27 papers), Vehicle emissions and performance (26 papers) and Fault Detection and Control Systems (23 papers). The work is most often cited by research in Control and Systems Engineering (2.5k citations), Computer Networks and Communications (1.9k citations), Geochemistry and Petrology (272 citations), Automotive Engineering (477 citations) and Computer Vision and Pattern Recognition (545 citations). Yu Kang has collaborated with scholars based in China, Australia and Singapore. Frequent co-authors include Jiahu Qin, Wei Xing Zheng, Zhijun Li, Yun‐Bo Zhao, Yang Cao, Qichao Ma, Guijian Liu, Weiming Fu, Gaosheng Zhang and Wenjun Lv. Their work appears in journals such as IEEE Transactions on Cybernetics, IEEE Transactions on Industrial Electronics, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Artificial Intelligence and Neurocomputing.

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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