Chaoda Peng

523 citations
23 papers · 385 · h-index 12

Impact in

Papers in

Chaoda Peng

19 papers receiving 379 citations

Peers

Chaoda Peng
Comparison fields: 5 of 44
  • Computational Theory and Mathematics 217
  • Artificial Intelligence 217
  • Computer Vision and Pattern Recognition 81
  • Industrial and Manufacturing Engineering 37
  • Aerospace Engineering 86
Replace Tim Hendtlass with:
Tim Hendtlass Australia
Nengxian Liu China
Shoufei Han China
Zhu Qingbao China
Ruwang Jiao China
Yintong Li China
Karin Zielinski Germany
Doaa El-Shahat Egypt
Cristian Ramirez‐Atencia Spain
Chaoda Peng relative to Tim Hendtlass Australia Tim Hendtlass's profile →
Citations per field
00.5×10×14.1×
Tim Hendtlass · 1×
Citations per year

Countries citing papers authored by Chaoda Peng

Since Specialization
Citations

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

Fields of papers citing papers by Chaoda Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201783
2 202247
3 202241
4 202037
5 201732
6 202330
7 202019
8 202417
9 201517
10 202313
11 202112
12 202311
13 201610
14 20157
15 20243
16 20233
17 20251
18 20171
19 20161
20 20250

About Chaoda Peng

Chaoda Peng is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications, Computer Vision and Pattern Recognition and Aerospace Engineering, having authored 23 papers that have together received 385 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (16 papers), Advanced Multi-Objective Optimization Algorithms (14 papers), Evolutionary Algorithms and Applications (8 papers), UAV Applications and Optimization (3 papers), Robotic Path Planning Algorithms (2 papers), Air Traffic Management and Optimization (2 papers), Optimal Experimental Design Methods (2 papers) and Advanced Chemical Sensor Technologies (1 paper). The work is most often cited by research in Computational Theory and Mathematics (217 citations), Artificial Intelligence (217 citations), Computer Vision and Pattern Recognition (81 citations), Industrial and Manufacturing Engineering (37 citations) and Aerospace Engineering (86 citations). Chaoda Peng has collaborated with scholars based in China, Macao and United States. Frequent co-authors include Hai‐Lin Liu, Fangqing Gu, Erik D. Goodman, Jiawen Kang, Yuan Wu, Xumin Huang, Long Qi, Jinrong Cui, Yuan Yuan and Shengli Xie. Their work appears in journals such as IEEE Internet of Things Journal, Applied Soft Computing, IEEE Transactions on Evolutionary Computation, IEEE Wireless Communications Letters and IEEE Transactions on Intelligent Transportation 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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