Ke Chen

3.1k citations
103 papers · 2.3k · h-index 26

Impact in

Papers in

    • Metaheuristic Optimization Algorithms Research 27
    • Evolutionary Algorithms and Applications 16
    • Sentiment Analysis and Opinion Mining 4
    • Text and Document Classification Technologies 3
    • Advanced Multi-Objective Optimization Algorithms 21

Ke Chen

87 papers receiving 2.3k citations

Peers

Ke Chen
Comparison fields: 5 of 146
  • Artificial Intelligence 1.0k
  • Computational Theory and Mathematics 480
  • Control and Systems Engineering 289
  • Computer Vision and Pattern Recognition 228
  • Cancer Research 113
Replace Yumin Chen with:
Yumin Chen China
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Zhiwei Ji China
Fei Han China
Qasem Al-Tashi Malaysia
Pengfei Zhang China
Meng Sun China
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Ke Chen relative to Yumin Chen China Yumin Chen's profile →
Citations per field
00.5×2×3×3.6×
Yumin Chen · 1×
Citations per year

Countries citing papers authored by Ke Chen

Since Specialization
Citations

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

Fields of papers citing papers by Ke Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 103 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020222
2 2020205
3 2017175
4 2019171
5 2017152
6 2020118
7 202080
8 202275
9 202468
10 201856
11 201552
12 202145
13 202241
14 201539
15 202039
16 202139
17 202338
18 202237
19 202237
20 201734

About Ke Chen

Ke Chen is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Control and Systems Engineering, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition, having authored 103 papers that have together received 2.3k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (27 papers), Advanced Multi-Objective Optimization Algorithms (21 papers), Evolutionary Algorithms and Applications (16 papers), Advanced Algorithms and Applications (6 papers), Sentiment Analysis and Opinion Mining (4 papers), Energy Load and Power Forecasting (4 papers), Smart Grid Energy Management (4 papers) and Text and Document Classification Technologies (3 papers). The work is most often cited by research in Artificial Intelligence (1.0k citations), Computational Theory and Mathematics (480 citations), Control and Systems Engineering (289 citations), Computer Vision and Pattern Recognition (228 citations) and Cancer Research (113 citations). Ke Chen has collaborated with scholars based in China, New Zealand and United States. Frequent co-authors include Fengyu Zhou, Xianfeng Yuan, Fengyu Zhou, Bing Xue, Mengjie Zhang, Yugang Wang, Kunjie Yu, Jing Liang, Caitong Yue and Gang Chen. Their work appears in journals such as IEEE Transactions on Evolutionary Computation, Knowledge-Based Systems, Expert Systems with Applications, Applied Soft Computing and IEEE Transactions on Systems Man and Cybernetics 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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