Hanbing Qu

30 papers receiving 241 citations

Peers

Hanbing Qu
Comparison fields: 5 of 59
  • Energy Engineering and Power Technology 12
  • Computer Vision and Pattern Recognition 70
  • Safety, Risk, Reliability and Quality 27
  • Control and Systems Engineering 58
  • Electrical and Electronic Engineering 103
Replace Junjie Jia with:
Junjie Jia China
Sobia Baig Pakistan
Mohammed Mestari Morocco
Sudha Gupta India
Kiran Sultan Saudi Arabia
Qiang Lu China
Adrián González Mexico
Hagbae Kim South Korea
Zhenhui Ye China
Zhixi Shen China
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Countries citing papers authored by Hanbing Qu

Since Specialization
Citations

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

Fields of papers citing papers by Hanbing Qu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201239
2 200934
3 201629
4 201827
5 202027
6 202314
7 201610
8 20179
9 20239
10 20097
11 20147
12 20254
13 20204
14 20093
15 20123
16 20163
17 20193
18 20142
19 20132
20
Variational bayes learning for models with linear equality constraints
20131

About Hanbing Qu

Hanbing Qu is a scholar working on Electrical and Electronic Engineering, Control and Systems Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition and Safety, Risk, Reliability and Quality, having authored 35 papers that have together received 247 indexed citations. Recurring topics across this work include Optimal Power Flow Distribution (11 papers), Power System Optimization and Stability (7 papers), Microgrid Control and Optimization (6 papers), Advanced Image and Video Retrieval Techniques (5 papers), Power System Reliability and Maintenance (5 papers), Robotics and Sensor-Based Localization (4 papers), Energy Load and Power Forecasting (3 papers) and HVDC Systems and Fault Protection (3 papers). The work is most often cited by research in Energy Engineering and Power Technology (12 citations), Computer Vision and Pattern Recognition (70 citations), Safety, Risk, Reliability and Quality (27 citations), Control and Systems Engineering (58 citations) and Electrical and Electronic Engineering (103 citations). Hanbing Qu has collaborated with scholars based in China and United States. Frequent co-authors include Yutian Liu, Bao-Gang Hu, Jiaqiang Wang, Yong Wang, Shuang-Hong Yang, Zhen Zhou, Ming Yu, Bin Li, Jiaqiang Wang and Zhi Li. Their work appears in journals such as International Journal of Electrical Power & Energy Systems, IEEE Access, Ecological Informatics, Information Sciences and IEEE Transactions on Pattern Analysis and Machine Intelligence.

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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