智能过程系统工程教育部工程研究中心

韩永明,副教授,硕士生导师

发布人:信息学院发布时间:2020-03-31浏览次数:369

照片+个人介绍

韩永明:副教授,硕士生导师;20146月北京化工大学控制理论与控制工程博士毕业,留校任教,同时在化学工程学院入职博士后,20166月博士后出站作为北京化工大学“青年后备引进人才”留校任教,20175月入选北京化工大学“青年英才百人计划”,现任中国自动化学会会员、中国化工学会专业会员和北京自动化学会会员。研究领域包括系统建模及优化、能效评价、数据分析与信息集成、智能优化方法等。近五年,以第一作者/通讯联系人发表学术论文70余篇(SCI/EI收录60余篇:总影响因子214.278,中科院/JCR一区18篇,二区20 篇(TOP 33篇,ESI高被引3篇、中国化工学会2014-2018高被引论文1篇),授权发明专利5项,申请专利20项,主持国家自然科学基金面上、青年项目和北京市优秀人才培养资助计划,参与国家重点研发计划、国家自然科学基金重点项目等十余项目。分别获得北京市科协2020-2022年度青年人才托举计划、2019年《Energy and Built Environment》青年学术新人提名奖,2018年北京自动化学会“青年科技创新人才”奖等。


主要科研项目 Research Projects

项目名称

项目来源

复杂石化过程能量系统建模与优化关键技术研究

国家自然科学基金委员会,面上项目

基于DEA的复杂化工过程能效分析与预测方法研究

国家自然科学基金委员会,青年项目

复杂石化工业能效多层次评价方法研究与应用

北京市优秀人才培养资助计划项目

大型建筑多层次能效评价与资源配置

北京市科协金桥工程种子资金C类项目


主要论文Research Paper

  1. Geng, Z., Zhang, Y., Li, C., Han, Y.*, Cui, Y., & Yu, B. Energy optimization and prediction modeling of petrochemical industries: An improved convolutional neural network based on cross-feature. Energy,  2020, 194: 116851.

  2. Zhiqiang Geng , Ning Chen, Yongming Han , Bo Ma*. An improved intelligent early warning method based on MWSPCA and its application in complex chemical processes. The Canadian Journal of Chemical Engineering.   

  3. Yongming Han, Rundong Zhou , Zhiqiang Geng* , Ju Bai , Bo Ma *, Jinzhen Fan. A novel data envelopment analysis cross-model integrating interpretative structural model and analytic hierarchy process for energy efficiency evaluation and optimization modeling: Application to Ethylene IndustriesJournal of Cleaner Production 246 (2020): 118965

  4. Yongming Han, Shuheng Zhang, Zhiqiang Geng*, Qin Wei, Zhi Ouyang. Level Set based Shape Prior and Deep Learning for Image Segmentation[J]. IET Image Processing. 2020, 14(1): 183-191.

  5. Zhiqiang Geng , Guofei Chen, Yongming Han , Fang Li, Gang Lu, Qing Wei*.  Semantic relation extraction using sequential and tree-structured LSTM with attention. Information Sciences  509 (2020) 183–192  .  

  6. Bo Ma#, Yongming Han#,*, Shiying Cui, Zhiqiang Geng*, Hongda Li, Chong Chu. Risk early warning and control of food safety based on an improved analytic hierarchy process integrating quality control analysis method. Food Control. 108(2020), 106824.  

  7. Yongming Han, Chenyu Fan, Meng Xu, Zhiqiang Geng*, Yanhua Zhong. Production capacity analysis and energy saving of complex chemical processes using LSTM based on attention mechanism. Applied Thermal Engineering. 2019, 160, 114072.

  8. Yunfei Cui#, Yongming Han#, Zhiqiang Geng*; Qunxiong Zhu*, Jinzhen Fan, Production Optimization and Energy Saving of Complex Chemical Processes using Novel Competing Evolutionary Membrane Algorithm: Emphasis on Ethylene Cracking. Energy Conversion and Management, 196 (2019) 311–319.

  9. Yongming Han, Shiying Cui, Zhiqiang Geng*, Chong Chu, Kai chen, Yajie Wang. Food quality and safety risk assessment using a novel HMM method based on GRA.Food Control 105 (2019) 180–189

  10. Zhiqiang Geng, Rongfu Zeng, Yongming Han *, Yanhua Zhong, Hua Fu. Energy efficiency evaluation and energy saving based on DEA integrated affinity propagation clustering: Case study of complex petrochemical industries. Energy, 2019,179: 863-875.

  11. Yongming Han, Chang Long, Zhiqiang Geng*, Qunxiong Zhu*, Yanhua Zhong. A novel DEACM integrating Affinity Propagation for performance evaluation and energy optimization modeling: Application to complex petrochemical. Energy Conversion and Management, 2019 183 , 349–359.  

  12. Zhiqiang Geng , Qingchao Meng, Ju Bai, Jie Chen, Yongming Han , Qing Wei*, Zhi Ouyang.  A model-free Bayesian classifier. Information Sciences  482(2019) 171–188 .    

  13. Xiaoyong Lin, Shiying Cui, Yongming Han*, ZhiqiangGeng*, Yanhua Zhong. An improved ISM method based on GRA for hierarchical analyzing theinfluencing factors of food safety. Food Control.2019,  99: 48-56

  14. Yongming Han, Hao Wu, Minghui Jia, Zhiqiang Geng*, Yanhua Zhong. Production capacity analysis and energy optimization of complex petrochemical industries using novel extreme learning machine integrating affinity propagations. Energy Conversion and Management, 2019, 99, 48–56.

  15. ZhiqiangGeng, Dirui Shang, Yongming Han*,Yanhua Zhong. Early warning modeling and analysis based on a deep radial basis function neural network integrating an analytic hierarchy process: A case study for food safety. Food Control.2019,96:329-342

  16. ZhiqiangGeng, Xuan Hu, Yongming Han*, Yanhua Zhong, A novel leakage detection method based on the sensitivity matrix of the pipe flow: Case study of water distribution systems. Journal of Water Resources Planning and Management. 2019, 145(2): 04018094-1-12

  17. ZhiqiangGeng, Xuan Hu, Ning Ding, Shanshan Zhao, Yongming Han*.A pattern recognition modeling approach based on the intelligent ensemble classifierApplication to identification and appraisal of water-flooded layers. Part I-Journal of Systems and Control Engineering.  2019, 233(7):737-750.

  18. ZhiqiangGeng, Zun Wang, Haixia Hu, Yongming Han*, Xiaoyong Lin*. A Fault Detection Method based on Horizontal Visibility Graph-Integrated Complex Networks: Application to Complex Chemical Processes. Canadian Journal of Chemical Engineering.2019:97(5):1129-1138.

  19. Yuan Xu, Mingqing Zhang, Liangliang Ye, Qunxiong Zhu , Zhiqiang Geng, Yan-Lin He, YongmingHan*. A novel prediction intervals method integrating an error & selffeedback extreme learning machine with particle swarm optimization for energy consumption robust prediction. Energy, 164 (2018) 137-146.  

  20. ZhiqiangGeng,HongdaLi,QunxiongZhu,YongmingHan*. Production prediction and energy-saving model based on Extreme Learning Machine integrated ISM-AHP: Application in complex chemical processes . Energy, 2018, 160: 898-909.  

  21. Zhiqiang Geng, Ju Bai, Deyang Jiang, Yongming Han*.Energy structure analysis and energy saving of complex chemical industries:A novel fuzzy interpretative structural model. Applied Thermal Engineering 142 (2018) 433–443.

  22. Yongming Han, Qing Zeng, Zhiqiang Geng*, Qunxiong Zhu*. Energy management and optimization modeling based on a novel fuzzy extreme learning machine: Case study of complex petrochemical industries. Energy Conversion and Management, 2018, 145, 41–52.

  23. Yongming Han, Chang Long, Zhiqiang Geng*, Keyu Zhang*. Carbon emission analysis and evaluation of industrial departments in China: An improved environmental DEA cross model based on information entropy[J]. Journal of Environmental Management, 2018, 205: 298-307.   

  24. Zhiqiang Geng, Yanan Li, Yongming Han*, Qunxiong Zhu*. A Novel Self-Organizing Cosine Similarity Learning Network: An Application to Production Prediction of Petrochemical Systems. Energy, 2018, 142: 400-410.  

  25. Zhiqiang Geng , Zhongkun Li  , Yongming Han .  A new deep belief network based on RBM with glial chains. Information Sciences 463–464 (2018) 294–306 .  

  26. Zhiqiang Geng, Jungen Dong, Yongming Han*, Qunxiong Zhu*. Energy and environment efficiency analysis based on an improved environment DEA cross-model: Case study of complex chemical processes. Applied Energy, 2017, 205, 465-476.

  27. Zhiqiang Geng, Huachao Gao, Yanqing Wang, Yongming Han*, Qunxiong Zhu*. Energy saving analysis and management modeling based on index decomposition analysis integrated energy saving potential method: Application to complex chemical processes. Energy Conversion and Management, 2017, 145, 41–52.

  28. Yunfei Cui, Zhiqiang Geng*, Qunxiong Zhu. Yongming Han*. Review: Multi-objective optimization methods and application in energy saving. Energy 2017, 125, 681-704

  29. Zhiqiang Geng, Xiao Yang, Yongming Han*, Qunxiong Zhu*. Energy optimization and analysis modeling based on extreme learning machine integrated index decomposition analysis: Application to complex chemical processes. Energy 2017,120, 67-78

  30. Zhiqiang Geng, Lin Qin, Yongming Han*, Qunxiong Zhu*. Energy saving and prediction modeling of petrochemical industries: A novel ELM based on FAHP. Energy 2017,122, 350-362 (TOP/SCI)  

  31. Yongming Han, Qunxiong Zhu, Zhiqiang Geng*, Yuan Xu*. Energy and carbon emissions analysis and prediction of complex petrochemical systems based on an improved extreme learning machine integrated interpretative structural model. Applied Thermal Engineering. 2017, 115, 280-291.

  32. Yongming Han, Zhiqiang Geng*, Yixin Qu, Qunxiong Zhu*. Linear optimization fusion model based on fuzzy C-means: Case study of energy efficiency evaluation in ethylene product. Journal of Analytical and Applied Pyrolysis 2017,125, 347–355

  33. Yaxun Chen, Yongming Han*, Qunxiong Zhu*. Energy and environmental efficiency evaluation based on a novel data envelopment analysis: An application in petrochemical industries. Applied Thermal Engineering. 2017, 119, 156-164.

  34. Zhiqiang Geng, Shanshan Zhao, Guangcan Tao, Yongming Han*. Early warning modeling and analysis based on analytic hierarchy process integrated extreme learning machine (AHP-ELM): Application to food safety. Food Control 2017, 78, 33-42.

  35. Zhiqiang Geng, Jungen Dong, Jie Chen, Yongming Han*. A new Self-Organizing Extreme Learning Machine soft sensor model and its applications in complicated chemical processes. A new Self-Organizing Extreme Learning Machine soft sensor model and its applications in complicated chemical processes. Engineering Applications of Artificial Intelligence. 2017, 62, 38-50.

  36. Zhiqiang Geng, Jie Chen, Yongming Han*. Energy Efficiency Prediction Based on PCA-FRBF Model: A Case Study of Ethylene Industries. IEEE Transactions on Systems Man Cybernetics-Systems. 2017, 47(8),1763-1773.

  37. Yongming Han, Zhiqiang Geng*, Qunxiong Zhu, Zun Wang, Yunfei Cui. Energy consumption analysis and evaluation of petrochemical industries using an improved fuzzy analytic hierarchy process approach. Journal of Intelligent & Fuzzy Systems. 2017,32(6),4183-4195.

  38. Zhiqiang Geng, Zun Wang, Chenglong Peng, Yongming Han*. A New Fuzzy Process Capability Estimation Method Based on Kernel Function and FAHP. IEEE Transactions on Engineering Management, 2016, 63(2): 177-188.

  39. Yongming Han, Zhiqiang Geng*, Zun Wang, Peng Mu. Performance analysis and optimal temperature selection of ethylene cracking furnaces: A data envelopment analysis cross-model integrated analytic hierarchy process. Journal of Analytical and Applied Pyrolysis 2016,122, 35–44

  40. Zhiqiang Geng, Zun Wang, Qunxiong Zhu, Yongming Han*. Multi-objective operation optimization of ethylene cracking furnace based on AMOPSO algorithm. Chemical Engineering Science. 2016,153, 21–33

  41. Yongming Han, Zhiqiang Geng *, Qunxiong, Zhu*. Energy optimization and prediction of complex petrochemical industries using an improved artificial neural network approach integrating data envelopment analysis. Energy Conversion and Management 2016,124, 73–83

  42. Yongming Han, Zhiqiang Geng*, Qunxiong Zhu*, Yixin Qu. Energy efficiency analysis method based on fuzzy DEA cross-model for ethylene production systems in chemical industry. Energy. 2015, 83, 685-695.

  43. Yongming Han, Zhiqiang Geng*, Xiangbai Gu*, Zun Wang. Performance Analysis of China Ethylene Plants by Measuring Malmquist Production Efficiency Based on an Improved Data Envelopment Analysis Cross-Model. Industrial & Engineering Chemistry Research 2015,54, 272-284.

  44. Yongming Han, Zhiqiang Geng*, Xiangbai Gu, Qunxiong Zhu*. Energy Efficiency Analysis based on DEA Integrated ISM: A Case Study for Chinese Ethylene Industries. Engineering Applications of Artificial Intelligence. 2015, 45, 80-89.

  45. Yongming Han, Zhiqiang Geng*, Qunxiong Zhu, Xiaoyong Lin. Energy consumption hierarchical analysis based on interpretative structural model for ethylene production. Chinese Journal of Chemical Engineering, 2015, 23(12): 2029-2036.

  46. Yongming Han, Zhiqiang Geng*. Energy Efficiency Hierarchy Evaluation based on Data envelopment analysis and its application in Petrochemical Process. Chemical Engineering & Technology, 2014, 37(12), 2085–2095

  47. Yongming Han, Zhiqiang Geng*, Qiyu Liu. Energy Efficiency Evaluation Based on Data Envelopment Analysis Integrated Analytic Hierarchy Process in Ethylene Production. Chinese Journal of Chemical Engineering 2014, 22(12), 1279-1284



科研成果

针对复杂石化过程节能降耗和环境减排问题,提出了基于数据融合的化工生产全流程能效评价与节能潜力分析方法。

  1. 针对石化过程能源消耗特点,提出了基于数据融合的全流程能效评价和多层次能效指标提取方法,建立了石化过程多层次能效指标体系。
















    2. 针对石化过程的投入产出综合数据,提出了基于数据包络分析(DEA)的化工过程能源与环境排放效率的评价方法。