Associate Professor
Director of Smart Energy and Intelligent Computing Group
Shenzhen Institute of Advanced Technology, Chinese Academy of Science
Research Areas
Smart grid and its integration of vehicle to grid service, renewable energy, electric vehicles batteries and energy storages, artificial intelligence methods for modelling and optimization, particular neural network modelling and metaheuristic optimisation with their applications to power system scheduling, load forecasting and intelligent manufacturing.
Education
2013.02~2017.03  PhD of Electronic and Electrical Engineering, Queen's University Belfast, Belfast, United Kingdom. · EPSRC International Doctoral Studentship · Thesis title: Advanced Computational scheduling methods for integrating plugin electric vehicles and renewable energy into power systems · Supervisors: Prof. Kang Li & Dr. Aoife Foley 
2010.09~2013.01  Master of Control Theory and Engineering, Shanghai University, Shanghai, China · Thesis title: Realtime analysis and implementation for hybrid industrial network for renewable energy system monitoring · Supervisors: Prof. Minrui Fei & Prof. Jingqi Fu · Top Ten graduates and academic star 
2006.09~2010.06  Bachelor of Automation, Shanghai University, Shanghai, China · Thesis title: Design and implementation for twolayers wireless industry network protocol for renewable energy system monitoring · Supervisor: Prof. Minrui Fei & Dr. Haikuan Wang · Top Ten student in Shanghai University

Experience
Work Experience
2017.09~ Present
Assistant Professor  Associate Professor, Director of Smart Energy and Intelligent Control Group, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences
• Lead a group with 2 research staffs, 2 PhD students and 3 MSc students
• Delivering lectures in multidisciplinary modules for MSc students
• Develop artificial intelligence approaches and optimisation/modelling technologies for renewable energy and mechatronics systems
• Successfully obtained a number of research grants
• Establish strong research links with domestic and international scholars
Publications
Papers
J1. G. Hou, L. Gong, Z. Yang*, J. Zhang, Multiobjective economic model predictive control for gas turbine system based on quantum simultaneous whale optimization algorithm, Energy Conversion and Management, 2020, 207: 112498（JCR Q1, IF=7.181）
J2. Z. Yang, K. Li, Y. Guo, S. Feng, Q. Niu, Y. Xue, A. Foley, A binary symmetric based hybrid metaheuristic method for solving mixed integer unit commitment problem integrating with significant plugin electric vehicles, Energy , 2019, 170: 889905;（JCR Q1, IF=5.537）
J3. Z. Yang, K. Liu, J. Fan, Y. Guo, Q. Niu, J. Zhang, A Novel Binary/Realvalued Pigeon Inspired Optimization for Economic/Environment Unit Commitment with Renewables and Plugin Vehicles, Science ChinaInformation Science (中国科学信息科学), 2019, 62: 070213;（JCR Q2, IF=2.731）
J4. Z. Yang, M. Mourshed, K. Liu, Y. Guo, S. Feng, A novel competitive swarm optimized RBF neural network model for shortterm solar power generation forecasting, Neurocomputing, accepted, （JCR Q1, IF=4.072）
J5. J. Zhu, Z. Yang*, M. Mourshed, Y. Guo, Y. Chang, Electric vehicle charging load forecasting: a comparative study of deep learning approaches, Energies, 12(14):2692; （JCR Q2, IF=2.707）
J6. Y. Wang, Z. Yang*, M. Mourshed, Y. Guo, Q. Niu, X. Zhu, Demand side management of plugin electric vehicles and coordinated unit commitment: A novel parallel competitive swarm optimization method, Energy Conversion and Management, 2019, 196,: 935949; （JCR Q1, IF=7.181）
J7. J. Zhu, Z. Yang*, Y. Guo, J. Zhang, H. Yang, Shortterm Load Forecasting for Electric Vehicle Charging Stations Based on Deep Learning Approaches, Applied Sciences, 2019, 9(9), 1723; （JCR Q2, IF=2.217）
J8. Y. Wang, Z. Yang*, Y. Guo, J. Zhu and X. Zhu, A Novel Binary Competitive Swarm Optimizer for Power System Unit Commitment, Applied Sciences, 9(9), 1776; （JCR Q2, IF=2.217）
J9. K. Liu, X. Hu, Z. Yang*, Y. Xie, S. Feng, Lithiumion battery charging management considering the economic costs of electricityloss and battery degradation, Energy Conversion and Management, 2019, 195: 167179; （JCR Q1, IF=7.181）
J10. Z. Yang, K. Li, Y. Guo, H. Ma, M. Zheng, Compact Realvalued TeachingLearning Based Optimization with the Applications to Neural Network Training, KnowledgeBased Systems, 2018, 159: 5162; （JCR Q1, IF=5.101）
J11. H. Ma, Z. Yang*, P. You, M. Fei, Multiobjective Biogeographybased Optimization for Dynamic Economic Emission Load Dispatch Considering Plugin Electric Vehicles Charging, Energy, 2017, Vol. 135:101111; （JCR Q1, IF=5.537）
J12. Z. Yang, K. Li, Q. Niu, Y. Xue, A novel parallelseries hybrid metaheuristic method for solving a hybrid unit commitment problem, KnowledgeBased Systems, 2017, 134:1330; （JCR Q1, IF=5.101）
J13. Z. Yang, K. Li, Q. Niu, Y. Xue, A comprehensive study of economic unit commitment of power systems integrating various renewable generations and plugin electric vehicles, Energy Conversion and Management, 2017, 132: 460481; （JCR Q1, IF=7.181）
J14. Z. Yang, K. Li, A. Foley, Computational Scheduling Methods for Integrating Plugin Electric Vehicles in the Power System: A Review, Renewable and Sustainable Energy Reviews, 2015, 51: 396416.; （JCR Q1, IF=10.556）
J15. Z. Yang, K. Li, Q. Niu, Y. Xue, A. Foley. A SelfLearning TeachingLearning Based Optimization for Dynamic Economic/Environmental Dispatch Considering Multiple Plugin Electric Vehicle Loads. Journal of Modern Power System and Clean Energy, 2014, 2(4): 298307; (Most citation award) （JCR Q2, IF=2.848）
J16. W. Liu, Z. Yang*, Kexin Bi, Forecasting the Acquisition of University Spinouts: An RBF Neural Network Approach, Complexity, 2017; （JCR Q1, IF=2.591）
J17. C. Li, H. Wu, Z. Yang*, Y. Wang, Z. Sun, SHLNN based Robust Control and Tracking for Hypersonic Vehicle under Parameter Uncertainty, Complexity, 2017; （JCR Q1, IF=2.591）
J18. Y. Guo, Z. Yang*, S. Feng, J. Hu, Complex power system status monitoring and evaluation using Big Data platform and Machine Learning algorithms: a review and a case study, Complexity, article ID 8496187, 2018; （JCR Q1, IF=2.591）
J19. 朱晓东，王颖，杨之乐*，郭媛君，启发式多目标优化算法在能源和电力系统中的典型应用综述，郑州大学学报（工学版），2019.09;
X. Zhu, Y. Wang, Z. Yang* and Y. Guo, A survey of featured applications of heuristic multiobjective optimization algorithms in power and energy systems, Journal of Zhengzhou University, 2019.09 (In Chinese);
J20. 杨之乐, 郑学理, 苏伟, 费敏锐, 付敬奇, 工业无线网络测控系统OPC数据服务器的设计实现, 计算机测量与控制, 2013. Vol 21 (04), pp 865869
Z. Yang, X. Zheng, W. Su, M. Fei, J. Fu, A design of OPC data server for industrial wireless network measurement system, Computer Measurement and Control, 2013. Vol 21 (04), pp 865869 (In Chinese)
J21. 杨之乐, 王秉臣, 费敏锐, 姚奇, 侯维岩, 基于令牌环的两层工业无线测控网络系统的设计与实现, 仪表技术, 2011.10
Z. Yang, B. Wang, M. Fei, Q. Yao, W. Hou, Design and implementation for a token based twolayers industrial wireless network control system, Instrumentation Technology, 2011.10 (In Chinese)
J22. L. Li, Y. Liu, Z. Yang, J. Tan, Method to improve convergence performance of iterative learning control systems with bounded noise, Journal of the Franklin Institute, 2020, 357: 16441670.
J23. Y. Xu, X. Li, X. Yang, Z. Yang, L. Wu, Q. Chen. A twostage model for ratedependent inverse hysteresis in reluctance actuators. Mechanical Systems and Signal Processing, 2020, 135: 106427.
J24. L. Yin, J. Chen, H. Zhang, Z. Yang, Q. Wan, L. Ning, J. Hu, Q. Yu, Improving emergency evacuation planning with mobile phone location data, Environment and Planning B: Urban Analytics and City Science, 2020;
J25. S Zhang, Z Yu, B Zhou, Z Yang, D Yang, A decentralized optimization strategy for distributed generators power allocation in microgrids based on load demandpower generation equivalent forecasting, Energies, 2020, 13(3): 648.
J26. Y. Xu, Z. Yang, X. Li and X. Yang, An Improved TeachingLearningbased Optimization Approach using Dynamic Opposite Learning, Knowledgebased systems, 2020, 104966;
J27. J. Lin, S. Feng, Z. Yang, Y. Zhang, Y. Zhang, A Novel Deep Neural Network Based Approach for Sparse Code Multiple Access, Neurocomputing, 2020, 382, 5263;
J28. B Zhou, X Yang, D Yang, Z Yang, T Littler, H Li, Probabilistic Load Flow Algorithm of Distribution Networks with Distributed Generators and Electric Vehicles Integration, Energies, 2020, 12(22), 124
J29. K. Xu, Z. Yang, Y. Xu, L. Feng, A Novel Interactive Fusion Method with Images and Point Clouds for 3D Object Detection. Applied Sciences, 2019, 9(6), 1065.
J30. Niu Q, Wang H, Sun Z, Z. Yang. An Improved Bare Bone MultiObjective Particle Swarm Optimization Algorithm for Solar Thermal Power Plants. Energies, 2019, 12(23): 4480.
J31. W. Liu, Y. Tao; Z. Yang; K. Bi, Exploring and visualizing the patent collaboration network: A case study of smart grid ﬁeld in China, Sustainability, 11(2), 465;
J32. Q Niu, K Jiang, Z Yang, An Improved, Negatively Correlated Search for Solving the Unit Commitment Problem's Integration with Electric Vehicles, Sustainability, 2019, 11 (24), 6945
J33. L. Zhang, Q. Li, Y. Guo, Z. Yang, L. Zhang, An investigation of wind direction and speed in a featured wind farm using joint probability distribution methods, Sustainability, 2019, 10(12), 4338;
J34. H. Ma, S. Shen, H. Ye, Z. Yang, M. Fei, H. Zhou, Multipopulation techniques in nature inspired optimization algorithms: A comprehensive survey, Swarm and Evolutionary Computation, 2019, 44: 365387;
J35. J. Na, Z. Yang, S. Kamal, L. Hu, W. Wang, Y. Zhou, BioInspired Learning and Adaptation for Optimization and Control of Complex Systems, Complexity, 2019, Editorial;
J36. F. Song, Y. Liu, X. Yang, H. Xu, P. He, Z. Yang, Iterative Learning Identification and Compensation of SpacePeriodic Disturbance in PMLSM Systems with Time Delay, IEEE Transactions on Industrial Electronics, 2018, 65 (9): 75797589;
J37. L. Li, Y. Liu, Z. Yang, X. Yang, K. Li, A meansquare error constrained approach to robust stochastic iterative learning control, IET Control Theory & Applications, 2018, 1(12): 38  44;
J38. H. Ma, D. Simon, P. Siarry, Z. Yang, M. Fei, BiogeographyBased Optimization: A 10Year Review, IEEE Transactions on Emerging Topics in Computational Intelligence, 2017, 10:391407;
J39. K. Liu, K. Li, Z. Yang, C. Zhang, J. Deng, An advanced Lithiumion battery optimal charging strategy, Electrochimica Acta, 2017, Vol. 225, 330344;
J40. T. Cheng, M. Chen, P. J. Fleming, Z. Yang, S. Gan, A novel hybrid teaching learning based multiobjective particle swarm optimization and its application in optimal placement of distributed generation, Neurocomputing, 2017, 222, 1225;
J41. H. Ma, M. Fei, Z. Yang. Biogeographybased optimization for identifying promising compounds in chemical process. Neurocomputing, 2016, 174: 494499;
J42. J. Yan, K. Li, E. Bai, Z. Yang, A. Foley, Time series wind power forecasting based on variant Gaussian Process and TLBO, Neurocomputing, 2016, 189:135–144;
J43. W. Liu, X. Xu, Z. Yang, J. Zhao and J. Xing, Impacts of FDI Renewable Energy Technology Spillover on China's Energy Industry Performance, Sustainability, 2016, 8, 846.;
J44. Y. Liu, Z. Chen, Z. Yang, K. Li, J. Tan, An Inline Surface Measurement Method for Membrane Mirror Fabrication Using Twostage Trained Zernike Polynomials and Elitist TeachingLearning Based Optimization, Measurement Science and Technology, 2016, 27(12): 124005;
J45. Y. Guo, K. Li, Z. Yang, J. Deng, D. Laverty, A novel radial basis function neural network principal component analysis scheme for PMUbased widearea power system monitoring, Electric Power Systems Research, 2015, 127: 197205;
J46. Z. Sun, K. Li, Z. Yang, Q. Niu, A. Foley , Impact of Electric Vehicles on a Carbon Constrained Power System  A post 2020 case study, Journal of Power and Energy Engineering, 2015, 3: 114122;
J47. L. Zhang, Q. Niu, Z. Yang and Kang Li, Integration of Electric Vehicles Charging in Unit Commitment, International Journal of Computer Science and Electronics Engineering, 2015, Vol.3, Iss.1, pp 2227;
J48. H. Ma, M. Fei, Z. Yang, H. Wang, Wireless networked learning control system based on Kalman filter and biogeographybased optimization method. Transactions of the Institute of Measurement and Control, 2014, Vol. 36(2) 224–236;
J49. 杨东升，王道浩，周博文，陈麒宇，杨之乐，胥国毅，崔明建，泛在电力物联网的关键技术与应用前景，发电技术 40 (2), 107114
J50. 朱俊丞，杨之乐，郭媛君，于坤杰，张建康，穆晓敏，深度学习在电力负荷预测中的应用综述，郑州大学学报（工学版），2019.09;
J. Zhu, Z. Yang, Y. Guo, J. Zhang, X. Mu, Deep Learning Applications in Power System Load Forecasting: a Survey, Journal of Zhengzhou University, 2019.09 (In Chinese);
J51. 吴帆, 杨之乐, 林小玲, 韩正之, 一种嵌入式无线车辆信息采集系统设计, 传感器与微系统, 2013, Vol. 32(02), pp 116118
F. Wu, Z. Yang, X. Lin, Z. Han, An embedded system based wireless data system for collecting vehicle information, Transducer and Microsystem technologies, 2013, Vol. 32(02), pp 116118. (In Chinese)
J52. 杨睿昕, 王任杰, 林小玲, 杨之乐, 基于无线磁阻传感器的车辆信息采集系统研究与实现, 仪表技术, 2011, Vol. 11, pp 2326
R. Yang, R. Yang, X. Lin, Z. Yang, Design and implementation of a wireless data system based on magnetoresistive sensor for vehicle data collection, Instrumentation Technology, 2011, Vol. 11, pp 2326 (In Chinese)
Conference papers
C1. Z. Yang, Y. Guo, Q. Niu, H. Ma, Y. Zhou and L. Zhang A Novel Binary Jaya Optimization for Economic/Emission Unit Commitment, in 2018 IEEE Congress on Evolutionary Computation (CEC), IEEE, 2018: 18;
C2. Z. Yang, Q. Niu, Y. Guo, H. Ma and B. Qu, A Fast Hybrid MetaHeuristic Algorithm for Economic/Environment Unit Commitment with Renewables and PlugIn Electric Vehicles, International Conference on Swarm Intelligence, 2018, 477486;
C3. Z. Yang, K. Li, X. Xu, A Hybrid Metaheuristic Method for Unit Commitment Considering Flexible Charging and Discharging of Plugin Electric Vehicles, in 2016 IEEE Congress on Evolutionary Computation (CEC), IEEE, 2016: 18;
C4. Z. Yang, K. Li, L. Zhang, Binary TeachingLearning Based Optimization for Power System Unit Commitment, 11th International Conference on Control (Control2016), IEEE, 2016: 18;
C5. Z. Yang, K. Li, Q. Niu, A. Foley, Unit Commitment Considering Multiple Charging and Discharging Scenarios of Plugin Electric Vehicles, in International Joint Conference on Neural Networks (IJCNN), IEEE, 2015: 18;
C6. Z. Yang, K. Li, A. Foley, and C. Zhang, Optimal scheduling methods to integrate plugin electric vehicles with the power system: a review, in Proceedings of the 19th world congress of the International Federation of Automatic Control (IFAC’14), Cape Town, South Africa. 2014: 2429;
C7. Z. Yang, K. Li, Q. Niu, C. Zhang, A. Foley, Nonconvex Dynamic Economic/Environmental Dispatch with Plugin Electric Vehicle Loads, in IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG), 2014. IEEE, 2014: 17;
C8. Z. Yang, K. Li, A. Foley, and C. Zhang, A new selflearning TLBO algorithm for RBF neural modelling of batteries in electric vehicles, in Evolutionary Computation (CEC), 2014 IEEE Congress on. IEEE, 2014: 26852691;
C9. Z. Yang, K. Li, Y. Guo, A New Compact TeachingLearningBased Optimization Method, Lecture Notes in Computer Science, Volume 8589, 2014, pp 717726;
C10. Z. Yang, M. Fei, W. Hou, B. Wang, The Design and Simulation of a TwoLayer Network Protocol for Industrial Wireless Monitoring and Control System, Communications in Computer and Information Science, Volume 323, 2012, pp 405413;
C11. Y. Wang, Z. Yang*, Y. Guo, J. Zhu and X. Zhu, A novel multiobjective competitive swarm optimization algorithm for multimodal multi objective problems, in 2019 IEEE Congress on Evolutionary Computation (CEC), IEEE, 2019: 18;
C12. J. Zhu, Z. Yang*, Y. Chang, Y. Guo and J. Zhang, A novel LSTM based deep learning approach for multitime scale electric vehicles charging load prediction, 2019 IEEE PES Innovative Smart Grid Technologies Asia, IEEE, 2019: 16;
C13. X Zhou, D Yang, B Zhou, Z Yang, Regional Adaptability and Economic Evaluation Based on Electric Vehicle Policy Analysis, 8th Renewable Power Generation Conference (RPG 2019), 2019 page (7 pp.)
C14. Y. Xu, X. Li, L. Wu, Z. Yang, P. Zhang, X. Yang, A direct inverse hysteresis model and its application in reluctance actuators. 2019 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 16
C15. W. Lin, Y. Guo, Z. Yang, J. Zhu, Y. Wang, Y. Liu, Y. Wang, A Novel Big Data Platform for City Power Grid Status Estimation, The Fourth International Conference on Data Mining and Big Data (DMBD’2019), 18
C16. W. Ding, Z. Yang and L. Feng, A Natural Scene Edge Detection Algorithm Based on Image Fusion, International Conference on Video and Image Processing (ICVIP 2018), IEEE, 2019: 17;
C17. K Xu, Z Yang, Y Xu, L Feng, Residual Blocks PointNet: A novel faster PointNet framework for segmentation and estimated pose, IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS 2018) , IEEE, 2018: 16;
C18. K. Xu, Z. Yang, B. Feng, A novel interactive fusion method with images and point clouds for 3D object detection, IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS 2018) , IEEE, 2018: 16; (Best student paper nominated)
C19. K. Deveerasetty, Y. Zhou, Z. Yang, Q. Wu, Robust control design for the trajectory tracking of a quadrotor, IEEE International Conference on Cyborg and Bionic Systems 2018, 351356
C20. F. Zhou, H. Wang, Z. Yang, Human localization and tracking system based on multi depth cameras in VR scene, IEEE International Conference on Cyborg and Bionic Systems 2018, 340345
C21. Z. Liu, X. Zeng and Z. Yang, Demand Based Bidding Strategies under Interval Demand for Integrated Demand and Supply Management in 2018 IEEE Congress on Evolutionary Computation (CEC), IEEE, 2018: 18;
C22. L. Zhang, K. Li, Z. Yang, X. Li, Y. Guo, D. Du and C. Wong, Compact Neural Modeling of Single Flow ZincNickel Batteries Based on Jaya Optimization, in 2018 IEEE Congress on Evolutionary Computation (CEC), IEEE, 2018: 18;
C23. Y. Guo, Z. Yang, Y. Zhou, J. Zhang and L. Zhang, Detection of Transient Signals in Smart Grid Using Artificial Neural Network Modeling and JAYA Optimization, 2018 IEEE PES Innovative Smart Grid Technologies Asia, IEEE, 2018: 16;
C24. Y. Zhou, Z. Yang, Y. Guo and Q. Wu, The College Compus Energy Monitoring Platform for Artificial Intelligence Application, 2018 IEEE PES Innovative Smart Grid Technologies Asia, IEEE, 2018: 16;
C25. F. Zhou, H. Wang, Z. Yang, A Novel 3D Head Multifeature Constraint Method for Human Localization based on Multiple Depth Cameras, IMIOT & ICSEE 2018, Communications in Computer and Information Science, 2018;
C26. Y Liu, Y Guo, Z Yang, J Hu, G Lu, Y Wang, Power system transmission line tripping analysis using a big data platform with 3D visualization, Computational Intelligence (SSCI), 2017 IEEE Symposium Series on, 18;
C27. Y. Liu, H. Luo, Z. Fu, Z. Yang and X. Yang, Integral Sliding Mode Based Precision Motion Control for PMLM, Communications in Computer and Information Science, 2017;
C28. F. Song, Y. Liu, X. Yang, Z. Yang and P. He, Iterative Learning Identification with Bias Compensation for Stochastic Linear TimeVarying Systems, Communications in Computer and Information Science, 2017;
C29. H. Ma, P. You, K. Liu, Z. Yang, M. Fei, Optimal Battery Charging Strategy Based on Complex System Optimization, Advanced Computational Methods in Energy, Power, Electric Vehicles, and Their Integration, 371378, Communications in Computer and Information Science, 2017;
C30. Z. Yang, Z. Yang, K. Li, W. Naeem, K. Liu, Heuristic Based Terminal Iterative Learning Control of ISBM Reheating Processes, Intelligent Computing, Networked Control, and Their Engineering Applications, Communications in Computer and Information Science, 2017;
C31. X. Li, K. Li, Z. Yang and C. K. Wong, A Novel RBF Neural Model for Single Flow Zinc Nickel Batteries, Communications in Computer and Information Science, 2017;
C32. X. Li, K. Li and Z. Yang, TeachingLearningFeedbackBased Optimization, International Conference on Swarm Intelligence (ICSI’2017), accepted;
C33. X. Li, C. K Wong and Z. Yang, A Novel Flowrate Control Method for Single Flow Zinc/Nickel Battery, International Conference for Students on Applied Engineering (ICSAE 2016). IEEE 2016: 3035.
C34. K. Liu, K. Li, Z. Yang, C. Zhang, J. Deng, Battery optimal charging strategy for a coupled thermoelectric model, in 2016 IEEE Congress on Evolutionary Computation (CEC) , 2016: 18;
C35. T. Cheng, M. Chen, P. J. Fleming, Z. Yang and S. Gan, An Effective PSOTLBO Algorithm for multiobjective Optimization, in 2016 IEEE Congress on Evolutionary Computation (CEC) , 2016: 18 (EI);
C36. L. Zhang, K. Li, Z. Yang, Z. Yang and Q. Wang TRIZ Based Teaching Strategy for Wind Turbine Control, 11th International Conference on Control (Control2016), IEEE, 2016: 18;
C37. H. Ma, Z. Yang, P. You and M. Fei, Complex System Optimization for Economic Emission Load Dispatch, 11th International Conference on Control (Control2016), IEEE, 2016: 18;
C39. C. Zhang, Z. Yang, and K. Li, Modeling of electric vehicle batteries using rbf neural networks, in The 2nd International Conference on Computing, Management and Telecommunications. IEEE, 2014, 116121;
C40. C. Zhang, K. Li, S. Mcloone, and Z. Yang, Battery modelling methods for electric vehicles a review, in 13th European Control Conference (ECC). IEEE, 2014, 26732678;
C41. C. Zhang, K. Li, Z. Yang, L. Pei, and C. Zhu, A new battery modelling method based on simulation error minimization, in IEEE Power and Energy Society General Meeting 2014. 16;
Students
现指导学生
杨猛 硕士研究生 085400电子信息