宋哲

宋哲，南京大學商學院教授，美國愛荷華大學（University of Iowa）工業工程博士、博士後。國際知名期刊IEEE Transactions on Sustainable Energy （國際電子電氣工程師協會會刊《可持續能源》，影響因子7.65，自引率7.6%）副主編。IEEE Power Engineering Society Letters, Industrial Engineering & Management編委成員。在美國留學期間參與多個被美國知名公司和機構資助的製造, 能源, 醫療等行業的系統, 決策優化項目, 這些公司和機構包括：Iowa Energy Center, John Deere, MidAmerican Energy, IAWIND, UIHC。在大數據分析建模和管理決策優化方向已經發表高影響因子國際期刊論文30多篇（均被SCI、EI索引，被引用2700多次；ESI近10年高被引論文一篇）, 獲中國美國發明專利13項。擔任十多個國際一流期刊的審稿人, 如 IEEE Trans. Industrial Informatics，European Journal of Operational Research、IEEE Trans. Industrial Electronics、IEEE Trans. Systems, Man, and Cybernetics等；INFORMS，IISE，IEEE協會會員。 ^[1] 

1.大數據分析與人工智能 （Big Data Analytics & AI）

2.複雜網絡建模與仿真（Complex Networks Modeling & Simulation）

3.創新與研發管理（Innovation, R&D Management）

4.智能製造（Intelligent Manufacturing）

5.智慧能源管理（Intelligent Energy Management）

6.風能智慧運營管理（Wind Power Intelligent O&M）

1. 大數據分析與管理決策優化

2. 創新與創業管理 ^[1] 

Kusiak Andrew,宋哲, 2016.8, 基本科學指標數據庫ESI 高被引論文, Web of Science

宋哲, 2016, 國家自然科學基金項目(#71001050)結題被評估為“優秀”, 國家自然科學基金委員會

宋哲, 2010.12, 科研新星獎, 南京大學商學院 ^[1] 

宋哲(PI), 2011-1 to 2013-12, 風電預測，併網調度與規劃的決策優化模型, 國家自然科學基金, 編號:71001050, 17.7萬元 ^[1] 

A. Kusiak, Zhe Song, November 5, 2013, DATA-DRIVEN APPROACH TO MODELING SENSORS WHEREIN OPTIMAL TIME DELAYS ARE DETERMINED FOR A FIRST SET OF PREDICTORS AND STORED AS A SECOND SET OF PREDICTORS, United States Patent Office Serial No. US 8,577,822 B2

A. Kusiak and Z. Song, 2009, Optimization in the Energy Industry: Improving Combustion Performance by Online Learning, P. Pardalos eds., Springer, ISBN: 978-3-540-88964-9. ^[1] 

1.Jeffrey Camm et al.;耿修林，宋哲 譯, 2017年3月, 商業數據分析(Essentials of Business Analytics), 機械工業出版社 數據科學、商務數量解析、商務智能系列教材 ^[1] 

1. G. Liang, Y. Su, F. Chen, H. Long, Z. Song and Y. Gan,2021, Wind Power Curve Data Cleaning by Image Thresholding Based on Class Uncertainty and Shape Dissimilarity, IEEE Transactions on Sustainable Energy, Early Access, SCI一區.

2. 蔡霞，宋哲等, 2020, 稠密網絡中的競爭創新擴散機制研究-以雙寡頭同時競爭擴散市場為例, 科學學與科學技術管理, CSSCI，國家自然科學基金委管理科學部重要期刊

3. X. Liu, Z. Zhang and Z. Song,2020, A comparative study of the data-driven day-ahead hourly provincial load forecasting methods: From classical data mining to deep learning, Renewable and Sustainable Energy Reviews, Vol. 119, 109632. SCI 一區, IF 12

4. 蔡霞，宋哲等, 2019, 動態稠密人際網絡中的創新擴散研究—基於多智能體仿真的分析, 《科技進步與對策》, CSSCI

5. 蔡霞，宋哲等, 2019, 社會網絡結構和採納者創新性對創新擴散的影響—以小世界網絡為例, 《軟科學》, CSSCI

6. 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.

7. 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.

8. 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一區.

9. 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

10. 蔡霞，宋哲等, 2016, 社會網絡環境下的創新擴散研究述評與展望, 科學學與科學技術管理, CSSCI，國家自然科學基金委管理科學部重要期刊

11. 蔡霞，宋哲等, 2017, 先發企業的崛起和後進企業的逆襲, 南開管理評論, CSSCI，國家自然科學基金委管理科學A類重要期刊（在管理學學科類目期刊中榮獲複合類、期刊綜合類和人文社科影響因子三項指標第一，影響力指數第二）

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 邀請稿（社評）

13. Zhe Song, Z. Zhang and X. Chen,2016, The decision model of 3-dimensional wind farm layout design, Renewable Energy, Vol.85 SCI，二區

14. 蔡霞，宋哲等, 2016, 基於自我保護動機的內隱建言信念對員工沉默的影響-一項中國情景的研究, 科學學與科學技術管理, CSSCI, 國家自然科學基金委管理科學部重要期刊

15. 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, 一區, Impact factor, 6.498

16. Z Song, Z. Zhang, X.L. Xu, C. Liu, 2015, An agent-based model to study the market dynamics of perpetual and subscription licensing, Journal of the Operational Research Society, 66:845-857SSCI/SCI, 三區

17. Z Song, Y Jiang, Z Zhang, 2014,Short-termwind speed forecasting with Markov-switching model, Applied Energy, 130SCI, 一區

18. 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，二區

19. Z. Zhang, Andrew Kusiak, Zhe Song, 2013,Scheduling electric power production at a wind farm, European Journal of Operational Research, Vol.224, pp. 227-238 SCI，二區

20. C. Xu, Z. Song, L.D. Chen and Y. Zheng,2011, Numerical investigation on porous media heat transfer in a solar tower receiver, Renewable Energy, Vol. 36, No. 3, pp. Vol. 36, No. 3, pp.1138-1144 SCI，二區

21. 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, 二區

22. A. Kusiak, W. Li and Z. Song,2010, Dynamic Control of Wind Turbines, Renewable Energy, Vol.35, No.2, pp.456-463 SCI, 二區

23. Z. Song and A. Kusiak, 2010, Mining Pareto-Optimal Modules for Delayed Differentiation, European Journal of Operational Research, Vol.201, No. 1, pp.123-128. SCI, 二區

24. 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, 一區

25. 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, 二區

26. 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, 二區

27. 程德俊，宋哲，王蓓蓓, 2010, 認知信任還是情感信任：高參與工作系統對組織創新績效的影響, 《經濟管理》,11期，pp81-90

28. Z. Song and A. Kusiak, 2009, Optimizing Product Configurations with a Data Mining Approach, International Journal of Production Research, Vol. 47, No. 7, pp. 1733-1751. SCI, 三區

29. 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, 二區

30. A. Kusiak, H. Zheng and Z. Song, 2009, On-Line Monitoring of Power Curves, Renewable Energy, Vol. 34, No. 6, pp.1487-1493. SCI, 二區

31. A. Kusiak, H. Zheng and Z. Song, 2009, Models for Monitoring Wind Farm Power, Renewable Energy, Vol. 34, No. 3, pp.583-590. SCI, 二區

32. 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, 二區

33. A. Kusiak and Z. Song, 2009, Sensor Fault Detection in Power Plants, ASCE Journal of Energy Engineering, Vol.135, No.4,pp.127-137SCI, 三區

34. 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, 二區

35. 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, 一區

36. 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, 二區

37. A. Kusiak, M.R. Smith and Z. Song, 2007, Planning Product Configurations Based on Sales Data, IEEE Transactions on Systems, Man and Cybernetics, Part C, Vol. 37, No. 4, pp. 602-609. SCI, 二區

38. 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, 一區

39. A. Kusiak and Z. Song, 2006, Combustion Efficiency Optimization and Virtual Testing: A Data-Mining Approach, IEEE Transactions on Industrial Informatics, Vol. 2, No. 3, pp. 176-184. SCI, 一區