1. Li, Y. and Tsung, F. (2009). “False Discovery Rate-Adjusted Charting Schemes for Multistage Process Monitoring and Fault Identification”. Technometrics, 51, 186-205. (SCI, impact factor= 1.711).
2. Jin, M., Li, Y. and Tsung, F. (2010) “Chart Allocation strategy for Serial-Parallel Multistage Manufacturing Processes”. IIE Transactions, 42(8), 577-588. (SCI, impact factor= 1.287).
3. Han, D, Tsung, F. and Li, Y. (2010) “A Nonlinear Filter Control Chart For Detecting Dynamic Changes”. Statistica Sinica, 20, 1077-1096. (SCI, impact factor= 0.956).
4. Han, D. and Tsung, F. , Li, Y. and Xian, J. (2010) “Detection of Changes in a Random Financial Sequence with a Stable Distribution ". Journal of Applied Statistics, 37(7), 1089-1111. (SCI, impact factor= 0.407).
5. Li, Y. and Tsung, F. (2011). “Chart Allocation Strategy for Serial Parallel_Multistage Manufacturing Processes with Multiple Faults”. Journal of the Chinese Institute of Industrial Engineers, 28(7),493-503.(EI)
6. Li, Y. and Tsung, F. (2011) “Detecting and Diagnosing Covariance Matrix Changes in Multistage Processes”. IIE Transactions, 43(4), 259-274. (SCI, impact factor=1.287).
7. Li, Y. and Tsung, F. (2012). “Multiple Attribute Control Charts with False Discovery Rate Control”. Quality and Reliability Engineering International, 28(8), 857-871. (SCI, impact factor=0.700)
8. Li, Y.; Liu, Y.; Zou, C. and Jiang, W. (2014).A Self-Starting Control Chart for High Dimensional Short-run Process. International Journal of Production Research. Int. J. of Production Research, Volume 52, Issue 2, 445-461.(SCI, impact factor=1.460)
9. Li, Y.; Su,Y. and Shu, L.(2014). An ARMAX model for forecasting the power output of a grid connected photovoltaic system. Renewable Energy. 66, 78-89. (SCI, impact factor=2.989)
10. Huang,W.,Jiang,W.,Wei, Q. and Li, Y. (2015).Projection-based Process Monitoring based on Empirical Divergence. IEEE Intelligent Systems Special Issue on System Informatics，IEEE Intelligent Systems,2015,30(6)：13-16..(SCI,impact factor=2.340)
11. Li, Y.; Shu,L. and Tsung, F.(2016). A False Discovery Approach for Scanning Spatial Disease Clusters with Arbitrary Shapes. IIE Transactions. Vol.48, No.7, 684-698.
12. Li, Y, Yong He, Yan Su, Lianjie Shu(2016).Forecasting the daily power output of a grid-connected photovoltaic system based on multivariate adaptive regression splines, Applied Energy, Volume 180, 392–401.(SCI, impact factor=5.746)
13. Wang,Z., Li, Y.*, Zhou, X. (2017).A Statistical Control Chart for Monitoring High Dimensional Poisson Data Streams. Quality and Reliability Engineering International.33（2）,307–321.
14. Li, Y. Liu, S. and Shu, L. (2018). Wind Turbine Fault Diagnosis Based on Gaussian Process Classifiers Applied to Operational Data. Renewable Energy. 66:78–89. (impact factor=6.274)
15. Fan, Jinyu; Shu, LJ; Yang, AJ; Li, YT （2020） Phase I analysis of high-dimensional covariance matrices based on sparse leading eigenvalues.JOURNAL OF QUALITY TECHNOLOGY. DOI: 10.1080/00224065.2020.1746212
16. Zhang, Y, Li, YT and Zhang, GY(2020) Short-term wind power forecasting approach based on Seq2Seq model using NWP data. Energy. Volume 213, 15，118371 （impact factor=6.082）.
17. Li, Y. Pei, D. and Wu, Z. (2020) "A Multivariate Non-Parametric Control Chart Based on Run Test
Computers & Industrial Engineering" . Computers & Industrial Engineering. Volume 149, November 2020, 106839。(impact factor=4.135)
18. Li, Y. Wu, Z. (2020) A condition monitoring approach of multi-turbine based on VAR model at farm level. Renewable Engergy Volume 166, Pages 66-80. (SCI, impact factor=2.989)
19.Li, Y. Jiang, W. Shu, L. (2021) Wind turbine fault diagnosis based on transfer learning and convolutional autoencoder with small-scale data. Renewable Energy, Accpeted.
20. Yanrong LI,Shizhe PENG,Yanting LI,Wei JIANG (2020). A review of condition-based maintenance: Its prognostic and operational aspects[J]. Frontiers of Engineering Management, 2020, 7(3): 323-334.
21. Lei Y, Li Y. A novel scheme of domain transfer in document-level cross-domain sentiment classification. Journal of Information Science. May 2021. doi:10.1177/01655515211012329