Jian-Yu Li

2.4k citations
90 papers · 1.6k indexed · 1 hit paper · h-index 19
Topics
Metaheuristic Optimization Algorithms Research (32 papers)Advanced Multi-Objective Optimization Algorithms (22 papers)Evolutionary Algorithms and Applications (18 papers)
Partner nations
ChinaSouth KoreaTaiwan

In The Last Decade

Jian-Yu Li

68 papers receiving 1.6k citations

Hit Papers

Evolutionary deep learning: A survey20222026202320242022255075100

Peers

Jian-Yu Li
Comparison fields: 5 of 125
  • Artificial Intelligence 917
  • Computational Theory and Mathematics 496
  • Computer Vision and Pattern Recognition 169
  • Electrical and Electronic Engineering 146
  • Industrial and Manufacturing Engineering 140
Replace Zhiyun Lin with:
Zhiyun Lin China
Qidi Wu China
Han Huang China
Hanning Chen China
Minghui Zhu United States
Genghui Li China
Xiaohui Hu China
Gabriel A. D. Lopes Netherlands
Jun Wu China
R. S. Ramakrishna South Korea
Jian-Yu Li relative to Zhiyun Lin China Zhiyun Lin's profile →
Citations per field
00.5×
Zhiyun Lin · 1×
Citations per year

Countries citing papers authored by Jian-Yu Li

Since Specialization
Citations

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

Fields of papers citing papers by Jian-Yu Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jian-Yu Li. 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 Jian-Yu Li. The network helps show where Jian-Yu Li may publish in the future.

Co-authorship network of co-authors of Jian-Yu Li

This figure shows the co-authorship network connecting the top 25 collaborators of Jian-Yu Li. A scholar is included among the top collaborators of Jian-Yu Li 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 Jian-Yu Li. Jian-Yu Li 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 0
2 1
3 0
4 0
5 0
6 0
7 7
8 0
9 4
10 4
11 2
12 1
13 0
14 5
15 13
16 18
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The research progress in speech compression coding technology
1
18
Study on simulation algorithm of metro train operation
1
19
Approximation of Function by Adaptively Growing Radial Basis Function Neural Networks
0
20 97

About Jian-Yu Li

Jian-Yu Li is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Industrial and Manufacturing Engineering, having authored 90 papers that have together received 1.6k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (32 papers), Advanced Multi-Objective Optimization Algorithms (22 papers) and Evolutionary Algorithms and Applications (18 papers). The work is most often cited by research in Computational Theory and Mathematics (496 citations), Artificial Intelligence (917 citations) and Industrial and Manufacturing Engineering (140 citations). Jian-Yu Li has collaborated with scholars based in China, South Korea and Taiwan. Frequent co-authors include Zhi‐Hui Zhan, Jun Zhang, Sam Kwong, Kay Chen Tan, Hua Wang, Yaping Huang, Chuan Wang, Hu Jin, Yu Guo and Yun Li. Their work appears in journals such as Journal of Membrane Science, Polymer and International Journal of Hydrogen Energy.

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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