代表性论文：
1. Shen, Y., Wang, T., & Song, Z.(2024). Online performance and proactive maintenance assessment of data driven prediction models. Journal of Intelligent Manufacturing, 1-35.
2. Liang, G., Su, Y., Wu, X., Ma, J., Long,H., & Song, Z. (2023). Abnormal data cleaning for wind turbines by image segmentation based on active shape model and class uncertainty. Renewable Energy, 216, 118965.
3. Shen, Y., Song, Z., Kusiak, A., & Zhan, Z. (2022). Prognosis of rotor parts fly-off based on cascade classification and online prediction ability index. Measurement Science and Technology, 34(1), 015122.
4. Shen, Y., Song, Z., & Kusiak, A.(2021). Enhancing the generalizability of predictive models with synergy ofdata and physics. Measurement Science and Technology, 33(3), 034002.
5. Liang, G., Su, Y., Chen, F., Long, H.,Song, Z., & Gan, Y. (2020). Wind power curve data cleaning by image thresholding based on class uncertainty and shape dissimilarity. IEEE Transactions on Sustainable Energy, 12(2), 1383-1393.
6. X. Liu, Z. Zhang and Z. Song,2020, Acomparative study of the data-driven day-ahead hourly provincial load forecasting methods: From classical data mining to deep learning, Renewableand Sustainable Energy Reviews, Vol. 119, 109632. SCI 一区, IF 12.
7. J. Zhu, Y. Shen, Z. Song, D. Zhou, Z.Zhang, and A. Kusiak, Data-Driven Building Load Profiling and Energy Management, Sustainable Cities and Society, Vol. 49, 2019, pp. 1-15.
8. Z. Song, Z. Zhang, Y. Jiang and J.Zhu,2018, Wind turbine health state monitoring based on a Bayesian data-driven approach, Renewable Energy, Vol. 125, pp.172-181.
9. Y. Jiang, H. Long, Z. Zhang and Zhe Song,2017, Day-ahead Prediction of Bi-hourly Solar Radiance with a Markov Switch Approach, IEEE Transactions on Sustainable Energy, Vol. 8, No. 4,pp.1536-1547, SCI一区.
10. L. Huan, Z. Zhang, Zhe Song, A.Kusiak,2017, Formulation and Analysis of Grid and Coordinate Models for Planning Wind Farm Layouts, IEEE Access, SCI, Vol. 5, pp.1810-1819.
11. 蔡霞，宋哲等, 2017, 先发企业的崛起和后进企业的逆袭,南开管理评论, CSSCI，国家自然科学基金委管理科学A类重要期刊（在管理学学科类目期刊中荣获复合类、期刊综合类和人文社科影响因子三项指标第一，影响力指数第二）.
12. Zhang Z. and Song Zhe, 2016, Mining SCADA Data Offers a New Roadmap of Wind Farm Operations and Management, Industrial Engineering & Management, Vol.5, No.2 邀请稿（社评）
13. Zhe Song, Z. Zhang and X. Chen,2016,The decision model of 3-dimensional wind farm layout design, Renewable Energy, Vol.85 SCI，二区.
14. Z. Zhang, Zhe Song and J. Xu,2015,Data-Driven Wind Turbine Power Generation Performance Monitoring, IEEE Transactions on Industrial Electronics, Vol. 62, No. 10 SCI, 一区, Impact factor, 6.498.
15.H. Long, L. Wang, Z. Zhang, Z. Song andJ. Xu (2015.10). “Data-driven wind turbine power generation performance monitoring,” IEEE Transactions On Industrial Electronics. Vol. 62:6627-6635.
16. Z Song, Y Jiang, Z Zhang,2014,Short-term wind speed forecasting with Markov-switching model, Applied Energy, 130SCI, 一区.
17. Yu Jiang, Zhe Song, Andrew Kusiak,2013,Very short-term wind speed forecasting with Bayesian structural break model, Renewable Energy, Vol. 50, Pp. 637-647 SCI，二区.
18. Z. Zhang, Andrew Kusiak, Zhe Song,2013,Scheduling electric power production at a wind farm, European Journalof Operational Research, Vol.224, pp. 227-238 SCI，二区.
19. C. Xu, Z. Song, L.D. Chen and Y.Zheng,2011, Numerical investigation on porous media heat transfer in a solartower receiver, Renewable Energy, Vol. 36, No. 3, pp. Vol. 36, No. 3, pp.1138-1144 SCI，二区.
20. Z. Song, X. Geng, A. Kusiak, and C.Xu,2011, Mining Markov Chain Transition Matrix from Wind Speed Time Series Data, Expert Systems with Applications, Vol. 38, No. 8, pp. Vol. 38, No.8, pp. 10229-10239 SCI, 二区.
21. A. Kusiak, W. Li and Z. Song,2010,Dynamic Control of Wind Turbines, Renewable Energy, Vol.35, No.2,pp.456-463 SCI, 二区.
22. Z. Song and A. Kusiak, 2010, Mining Pareto-Optimal Modules for Delayed Differentiation, European Journal ofOperational Research, Vol.201, No. 1, pp.123-128. SCI, 二区.
23. Z. Song and A. Kusiak, 2010,Multi-objective Optimization of Temporal Processes, IEEE Trans. Systems,Man, and Cybernetics, Part B, Vol.40, No.3, pp.845-856. SCI, 一区.
24. A. Kusiak and Z. Song,2010, Design of Wind Farm Layout for Maximum Wind Energy Capture, Renewable Energy,Vol.35, No. 3, pp. 685-694. SCI, 二区.
25. A. Kusiak, H. Zheng and Z. Song,2010,Power optimization of wind turbines with data mining and evolutionary computation, Renewable Energy, Vol. 35, No. 3, pp. 695-702. SCI, 二区.
26. Z. Song and A. Kusiak, 2009, Optimizing Product Configurations with a Data Mining Approach, International Journal ofProduction Research, Vol. 47, No. 7, pp. 1733-1751. SCI, 三区.
27. A. Kusiak, H. Zheng and Z. Song, 2009,Wind Farm Power Prediction: A Data-Mining Approach, Wind Energy, Vol.12, No.3, pp. 275-293 SCI, 二区.
28. A. Kusiak, H. Zheng and Z. Song, 2009,On-Line Monitoring of Power Curves, Renewable Energy, Vol. 34, No. 6,pp.1487-1493. SCI, 二区.
29. A. Kusiak, H. Zheng and Z. Song, 2009,Models for Monitoring Wind Farm Power, Renewable Energy, Vol. 34, No. 3,pp.583-590. SCI, 二区.
30. A. Kusiak, H. Zheng and Z. Song, 2009,Short-Term Prediction of Wind Farm Power: A Data Mining Approach, IEEE Transactions on Energy Conversion, Vol. 24, No. 1, pp. 125-136. SCI, 二区.
31. A. Kusiak and Z. Song, 2009, Sensor Fault Detection in Power Plants, ASCE Journal of Energy Engineering,Vol.135, No.4,pp.127-137SCI, 三区.
32. A. Kusiak, Z. Song and H. Zheng, 2009,Anticipatory Control of Wind Turbines with Data-Driven Predictive Models, IEEE Transactions on Energy Conversion, Vol. 24, No. 3, pp. 766-774. SCI, 二区.
33. Z. Song and A. Kusiak, 2009,Optimization of Temporal Processes: A Model Predictive Control Approach,IEEE Transactions on Evolutionary Computation, Vol. 13, No. 1, pp. 169-179.SCI, 一区.
34. A. Kusiak and Z. Song, 2008,Clustering-Based Performance Optimization of Boiler-Turbine System, IEEE Transactions on Energy Conversion, Vol.23, No. 2, pp. 651-658 SCI, 二区.
35. A. Kusiak, M.R. Smith and Z. Song,2007, Planning Product Configurations Based on Sales Data, IEEE Transactionson Systems, Man and Cybernetics, Part C, Vol. 37, No. 4, pp. 602-609. SCI, 二区.
36. Z. Song and A. Kusiak, 2007,Constraint-Based Control of Boiler Efficiency: A Data-Mining Approach, IEEE Transactions on Industrial Informatics, Vol. 3, No. 1, pp. 73-83.SCI, 一区.
37. A. Kusiak and Z. Song, 2006, CombustionEfficiency Optimization and Virtual Testing: A Data-Mining Approach, IEEE Transactions on Industrial Informatics, Vol. 2, No. 3, pp. 176-184. SCI, 一区.
