Pei-Qiu Huang

1.2k citations
26 papers · 938 indexed · 1 hit paper · h-index 13

Pei-Qiu Huang

26 papers receiving 929 citations

Hit Papers

Joint Deployment and Task Scheduling Optimization for Lar...241201920262021202350100150200

Peers

Pei-Qiu Huang
Comparison fields: 5 of 76
  • Computer Networks and Communications 461
  • Aerospace Engineering 418
  • Computer Vision and Pattern Recognition 225
  • Computational Theory and Mathematics 164
  • Artificial Intelligence 220
Replace Husheng Wu with:
Husheng Wu China
Håkan L. S. Younes United States
Farouk Kamoun Tunisia
Christian Buckl Germany
Junqi Zhang China
Jie Tian China
Mohammad Patwary United Kingdom
Francesco Martinelli Italy
Pei-Qiu Huang relative to Husheng Wu China Husheng Wu's profile →
Citations per field
00.5×3.8×
Husheng Wu · 1×
Citations per year

Countries citing papers authored by Pei-Qiu Huang

Since Specialization
Citations

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

Fields of papers citing papers by Pei-Qiu Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pei-Qiu Huang. 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 Pei-Qiu Huang. The network helps show where Pei-Qiu Huang may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20247
2 202418
3 20245
4 20241
5 20247
6 20239
7 20231
8 20238
9 202210
10 202211
11 202115
12 202086
13 202034
14 202028
15 201997
16 201946
17 201931
18 20186
19 201812
20 2018121

About Pei-Qiu Huang

Pei-Qiu Huang is a scholar working on Computational Theory and Mathematics, Computer Networks and Communications and Artificial Intelligence, having authored 26 papers that have together received 938 indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (13 papers), Metaheuristic Optimization Algorithms Research (11 papers), UAV Applications and Optimization (6 papers), IoT and Edge/Fog Computing (5 papers), Advanced Wireless Communication Technologies (4 papers), Evolutionary Algorithms and Applications (4 papers), Distributed Control Multi-Agent Systems (3 papers) and Advanced MIMO Systems Optimization (3 papers). The work is most often cited by research in Computer Networks and Communications (461 citations), Aerospace Engineering (418 citations) and Computer Vision and Pattern Recognition (225 citations). Pei-Qiu Huang has collaborated with scholars based in China, United Kingdom and Hong Kong. Frequent co-authors include Yong Wang, Kezhi Wang, Zhizhong Liu, Kun Yang, Muhammad Asim, Bing-Chuan Wang, Yu Zhou, Qingfu Zhang, Fei Li and Liang Wang. Their work appears in journals such as Information Sciences, IEEE Transactions on Vehicular Technology and IEEE Transactions on Cybernetics.

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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