Yan‐Feng Li

6.9k citations
198 papers · 5.5k indexed · 3 hit papers · h-index 41

Yan‐Feng Li

193 papers receiving 5.3k citations

Hit Papers

A novel deep convolutional neural network-bootstrap in...1532018202620202023100200300

Peers

Yan‐Feng Li
Comparison fields: 5 of 140
  • Statistics, Probability and Uncertainty 2.2k
  • Safety, Risk, Reliability and Quality 2.1k
  • Software 798
  • Medical Laboratory Technology 113
  • Statistics and Probability 530
Replace Hong‐Zhong Huang with:
Hong‐Zhong Huang China
Weiwen Peng China
Mohammad Modarres United States
Xiaosheng Si China
Wenbin Wang China
Dragan Banjević Canada
Bin Liu China
Rui Kang China
Nagi Gebraeel United States
Haitao Liao United States
Yan‐Feng Li relative to Hong‐Zhong Huang China Hong‐Zhong Huang's profile →
Citations per field
00.5×1.5×
Hong‐Zhong Huang · 1×
Citations per year

Countries citing papers authored by Yan‐Feng Li

Since Specialization
Citations

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

Fields of papers citing papers by Yan‐Feng Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yan‐Feng 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 Yan‐Feng Li. The network helps show where Yan‐Feng Li may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20254
2 20250
3 20251
4 20250
5 20243
6 20247
7 20243
8 20241
9 20241
10 20244
11 202319
12 202325
13 20231
14 20234
15 202115
16 20213
17 201965
18 20183
19 201731
20 201563

About Yan‐Feng Li

Yan‐Feng Li is a scholar working on Statistics, Probability and Uncertainty, Software and Safety, Risk, Reliability and Quality, having authored 198 papers that have together received 5.5k indexed citations. Recurring topics across this work include Reliability and Maintenance Optimization (59 papers), Probabilistic and Robust Engineering Design (54 papers), Risk and Safety Analysis (46 papers), Software Reliability and Analysis Research (33 papers), Fatigue and fracture mechanics (27 papers), Machine Fault Diagnosis Techniques (19 papers), Statistical Distribution Estimation and Applications (14 papers) and Engineering Diagnostics and Reliability (13 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (2.2k citations), Safety, Risk, Reliability and Quality (2.1k citations) and Software (798 citations). Yan‐Feng Li has collaborated with scholars based in China, United States and France. Frequent co-authors include Hong‐Zhong Huang, Hong‐Zhong Huang, Jinhua Mi, Weiwen Peng, Yuan‐Jian Yang, Cheng‐Geng Huang, Ning‐Cong Xiao, Yu Liu, Huaming Qian and Shun‐Peng Zhu. Their work appears in journals such as IEEE Transactions on Industrial Electronics, Expert Systems with Applications and International Journal for Numerical Methods in Engineering.

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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