Ling Zhu

59 papers receiving 395 citations

Peers

Ling Zhu
Comparison fields: 5 of 70
  • Electrical and Electronic Engineering 190
  • Control and Systems Engineering 170
  • Renewable Energy, Sustainability and the Environment 82
  • Artificial Intelligence 73
  • Computer Vision and Pattern Recognition 59
Replace Suresh Kumar Gawre with:
Suresh Kumar Gawre India
N. Kanagaraj Saudi Arabia
Shiue‐Der Lu Taiwan
Rajab Challoo United States
Juan Manuel Escaño Spain
A. Bhuvanesh India
Montaser Abdelsattar Egypt
Rania M. Ghoniem Saudi Arabia
Ling Zhu relative to Suresh Kumar Gawre India Suresh Kumar Gawre's profile →
Citations per field
00.5×
Suresh Kumar Gawre · 1×
Citations per year

Countries citing papers authored by Ling Zhu

Since Specialization
Citations

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

Fields of papers citing papers by Ling Zhu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ling Zhu

This figure shows the co-authorship network connecting the top 25 collaborators of Ling Zhu. A scholar is included among the top collaborators of Ling Zhu 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 Ling Zhu. Ling Zhu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 1
3 2
4 0
5 3
6 0
7 0
8 1
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10 0
11 14
12 2
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14 9
15 6
16 4
17
Simulation of shunt hybrid active power filter
0
18
Research on the Topology of Hybrid Cascaded Multilevel Converters
4
19
HARMONIC ANALYSIS AND OUTPUT FILTER DESIGN FOR MULTILEVEL PWM INVERTERS
5
20
on-line Detecting of Rotor Bar Breaking Fault for squirrel cage Asynchronous Motors
0

About Ling Zhu

Ling Zhu is a scholar working on Energy Engineering and Power Technology, Control and Systems Engineering and Ecological Modeling, having authored 75 papers that have together received 410 indexed citations. Recurring topics across this work include Microgrid Control and Optimization (12 papers), Photovoltaic System Optimization Techniques (11 papers) and Power Systems and Renewable Energy (11 papers). The work is most often cited by research in Energy Engineering and Power Technology (42 citations), Control and Systems Engineering (170 citations) and Renewable Energy, Sustainability and the Environment (82 citations). Ling Zhu has collaborated with scholars based in China, United States and Switzerland. Frequent co-authors include Guangyu Liu, Weijie Yu, Zongyi Wang, Qi Wang, Wei Li, Jiajun Wang, Yuan Guo, Zaijun Wu, Xiangjun Quan and Qinran Hu. Their work appears in journals such as IEEE Transactions on Industrial Electronics, Journal of Materials Chemistry A 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.

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