宋哲

宋哲,南京大学工商管理系副教授,美国爱荷华大学工业工程博士、博士后。专注于能源管理,工业大数据分析和系统优化。国际知名期刊 IEEE Transactions on Sustainable Energy (国际电子电气工程师协会会刊 《可持续能源》) 副主编。Industrial Engineering & Management编委成员。 在美国留学期间参与多个被美国知名公司和机构资助的能源管理、大众化定制、定制化医疗项目, 这些公司和机构包括:Iowa Energy Center, John Deere, MidAmerican Energy, IAWIND, UIHC。 在能源管理、大数据分析和管理决策优化方向已经发表国际期刊论文20多篇(均被SCI, EI索引,被引用1500多次), 书章节一张, 担任十多个国际期刊的审稿人, 如 IEEE Trans. Industrial Informatics,European Journal of Operational Research,IEEE Trans. Industrial Electronics,IEEE Trans. Systems, Man, and Cybernetics, Part A,Knowledge and Information Systems, Production Planning and Control, International Journal of Manufacturing Research. INFORMS,IIE,IEEE协会会员.

研究方向

  1. 能源管理
  2. 创新与创业管理
  3. 大数据分析

教学方向

  1. 数据模型与决策
  2. 创新与创业管理
  3. 大数据分析
进入教师园地>>

联系方式

南京大学商学院工商管理系,汉口路22号 210093, 电话: 025-8362-1041,办公室:1623. Email: zsong1(AT)nju.edu.cn

所获教学奖励

  1. 宋哲, 2016.9, 南京大学杜厦奖教金, 南京大学
  2. 徐小林,宋哲, 2016, Operations Management, 江苏省英文精品课程建设项目

所获科研奖励

  1. Kusiak Andrew,宋哲, 2016.8, 基本科学指标数据库ESI 高被引论文, Web of Science
  2. 宋哲, 2016, 国家自然科学基金项目(#71001050)结题被评估为“优秀”, 国家自然科学基金委员会
  3. 宋哲, 2010.12, 科研新星奖, 南京大学商学院

主持和参与科研项目

  1. 宋哲(PI), 2011-1 to 2013-12, 风电预测,并网调度与规划的决策优化模型, 国家自然科学基金, 编号:71001050, 17.7万元

出版专著

  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
  2. 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.

公开发表论文

  1. 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, Published Online
  2. 蔡霞,宋哲等, 2016, 社会网络环境下的创新扩散研究述评与展望, 科学学与科学技术管理, CSSI,国家自然科学基金委管理科学部重要期刊
  3. Zhang Zijun 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)
  4. 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
  5. 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
  6. 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, 66:845-857 SSCI/SCI, 三区
  7. Z Song, Y Jiang, Z Zhang, 2014, Short-term wind speed forecasting with Markov-switching model, Applied Energy, 130 SCI, 一区
  8. 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
  9. Zijun 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,二区
  10. 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,二区
  11. 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
  12. 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
  13. 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, 二区
  14. Z. Song and A. Kusiak, 2010, Multiobjective Optimization of Temporal Processes, IEEE Trans. Systems, Man, and Cybernetics, Part B, Vol.40, No.3, pp.845-856. SCI, 一区
  15. 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
  16. 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
  17. 程德俊,宋哲,王蓓蓓, 2010, 认知信任还是情感信任:高参与工作系统对组织创新绩效的影响, 《经济管理》, 11期,pp 81-90
  18. 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, 三区
  19. 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
  20. 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
  21. 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
  22. 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
  23. A. Kusiak and Z. Song, 2009, Sensor Fault Detection in Power Plants, ASCE Journal of Energy Engineering, Vol.135, No.4, pp.127-137 SCI, 三区
  24. 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
  25. 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
  26. 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
  27. 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, 二区
  28. 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
  29. 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, 一区

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