Yan‐Feng Li

6.9k total citations · 3 hit papers
198 papers, 5.5k citations indexed

About

Yan‐Feng Li is a scholar working on Statistics, Probability and Uncertainty, Safety, Risk, Reliability and Quality and Mechanics of Materials. According to data from OpenAlex, Yan‐Feng Li has authored 198 papers receiving a total of 5.5k indexed citations (citations by other indexed papers that have themselves been cited), including 88 papers in Statistics, Probability and Uncertainty, 66 papers in Safety, Risk, Reliability and Quality and 50 papers in Mechanics of Materials. Recurrent topics in Yan‐Feng Li's work include Reliability and Maintenance Optimization (59 papers), Probabilistic and Robust Engineering Design (54 papers) and Risk and Safety Analysis (46 papers). Yan‐Feng Li is often cited by papers focused on Reliability and Maintenance Optimization (59 papers), Probabilistic and Robust Engineering Design (54 papers) and Risk and Safety Analysis (46 papers). Yan‐Feng Li collaborates with scholars based in China, United States and France. Yan‐Feng Li's 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 and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, Expert Systems with Applications and International Journal for Numerical Methods in Engineering.

In The Last Decade

Yan‐Feng Li

193 papers receiving 5.3k citations

Hit Papers

A Bidirectional LSTM Prognostics Method Under Multiple Op... 2018 2026 2020 2023 2019 2018 2021 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yan‐Feng Li China 41 2.2k 2.1k 1.4k 1.2k 1.2k 198 5.5k
Hong‐Zhong Huang China 48 3.1k 1.5× 2.5k 1.2× 1.5k 1.1× 2.0k 1.6× 2.0k 1.7× 348 7.8k
Weiwen Peng China 30 1.2k 0.6× 1.5k 0.7× 1.4k 1.1× 1.1k 0.9× 935 0.8× 108 4.3k
Dragan Banjević Canada 27 876 0.4× 2.4k 1.1× 2.7k 2.0× 1.3k 1.0× 819 0.7× 79 5.4k
Mohammad Modarres United States 38 1.4k 0.7× 881 0.4× 1.3k 0.9× 957 0.8× 881 0.7× 264 5.5k
Hong‐Zhong Huang China 31 1.6k 0.7× 1.6k 0.8× 483 0.4× 598 0.5× 722 0.6× 151 3.4k
Xiaosheng Si China 36 1.2k 0.5× 4.3k 2.0× 3.2k 2.4× 1.2k 1.0× 962 0.8× 137 6.8k
Wenbin Wang China 26 890 0.4× 3.0k 1.4× 2.0k 1.5× 780 0.6× 570 0.5× 64 4.6k
Yu Liu China 33 1.4k 0.7× 1.7k 0.8× 547 0.4× 411 0.3× 457 0.4× 191 3.6k
Rui Kang China 31 1.2k 0.6× 1.5k 0.7× 806 0.6× 424 0.3× 370 0.3× 289 3.6k
Haitao Liao United States 35 1.1k 0.5× 2.6k 1.2× 1.2k 0.9× 556 0.5× 360 0.3× 198 4.8k

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 of co-authors of Yan‐Feng Li

This figure shows the co-authorship network connecting the top 25 collaborators of Yan‐Feng Li. A scholar is included among the top collaborators of Yan‐Feng 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 Yan‐Feng Li. Yan‐Feng 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
1.
Li, Yan‐Feng, et al.. (2025). Boosting thermal conductivity of boron nitride incorporated polymer composites via hydrogen bonding engineering. Materials Horizons. 12(17). 6765–6773. 4 indexed citations
2.
Huang, Xin, et al.. (2025). Reliability Assessment of MEMS Flow Sensors Considering Pollutant Deposition. Quality and Reliability Engineering International. 41(6). 2416–2426.
4.
Dou, Jun, Yaling Xun, Haifeng Yang, et al.. (2025). Multivariate time series forecasting based on time–frequency transform mixed convolution. Knowledge-Based Systems. 325. 113912–113912.
5.
Li, Yan‐Feng, et al.. (2024). An AK‐MCS‐based probabilistic fatigue life prediction framework for turbine disc with a mean stress correction model. Quality and Reliability Engineering International. 40(6). 3238–3252. 3 indexed citations
6.
Wang, Zhijian, Yan‐Feng Li, Lei Dong, et al.. (2024). A remaining useful life prediction framework with adaptive dynamic feedback. Mechanical Systems and Signal Processing. 218. 111595–111595. 7 indexed citations
7.
Lin, Zhifeng, et al.. (2024). Parameter identification of DEM-FEM coupling model to simulate traction behavior of tire-soil interaction. Journal of Terramechanics. 117. 101012–101012. 3 indexed citations
8.
Huang, Tudi, et al.. (2024). Probabilistic LCF life prediction framework for turbine discs considering random load history. Quality and Reliability Engineering International. 40(6). 3161–3172. 1 indexed citations
9.
Huang, Haitao, et al.. (2024). Vertebrobasilar dolichoectasia to trigeminal neuralgia: case report. Journal of Surgical Case Reports. 2024(1). rjad737–rjad737. 1 indexed citations
10.
Tang, Qianqian, Changming Wang, Kai Zheng, et al.. (2024). A prospective cohort study on perioperative percutaneous balloon compression for trigeminal neuralgia: safety and efficacy analysis. Neurosurgical Review. 47(1). 86–86. 4 indexed citations
11.
Li, Yan‐Feng, et al.. (2023). AGP-MCS+D: An active learning reliability analysis method combining dependent Gaussian process and Monte Carlo simulation. Reliability Engineering & System Safety. 240. 109541–109541. 19 indexed citations
12.
Huang, Tudi, et al.. (2023). A probabilistic fatigue life prediction method under random combined high and low cycle fatigue load history. Reliability Engineering & System Safety. 238. 109452–109452. 25 indexed citations
15.
Huang, Hong‐Zhong, et al.. (2021). Fatigue Life Prediction of Rolling Bearings Based on Modified SWT Mean Stress Correction. Chinese Journal of Mechanical Engineering. 34(1). 15 indexed citations
16.
Li, Yan‐Feng, et al.. (2021). Reliability Modeling and Analysis of Multi-Degradation of Momentum Wheel Based on Copula Function. Applied Sciences. 11(23). 11563–11563. 3 indexed citations
17.
Qian, Huaming, Hong‐Zhong Huang, & Yan‐Feng Li. (2019). A novel single-loop procedure for time-variant reliability analysis based on Kriging model. Applied Mathematical Modelling. 75. 735–748. 65 indexed citations
18.
Li, Yan‐Feng, et al.. (2018). Reliability analysis for fatigue damage of railway welded bogies using Bayesian update based inspection. Smart Structures and Systems. 22(2). 193–200. 3 indexed citations
19.
Huang, Hong‐Zhong, et al.. (2017). Fatigue Life Prediction of Fan Blade Using Nominal Stress Method and Cumulative Fatigue Damage Theory. International Journal of Turbo and Jet Engines. 37(2). 135–139. 31 indexed citations
20.
Li, Yan‐Feng, Jinhua Mi, Yu Liu, Yuan‐Jian Yang, & Hong‐Zhong Huang. (2015). Dynamic fault tree analysis based on continuous-time Bayesian networks under fuzzy numbers. Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability. 229(6). 530–541. 63 indexed citations

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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