研究领域
主要研究方向为+AI的跨学科工业场景基础研究及产业应用，包括人工智能及大模型在建筑、制造、能源等领域中的应用。
个人简介
杨之乐，中国科学院青年创新促进会会员，深圳市优青。主要研究方向为人工智能方法在能源、电力、视觉、交通、智能制造等领域中的应用，包括基于数据的启发式优化与神经网络建模等计算智能方法，主持包括国家自然科学基金、中国科学院青年创新促进会人才项目、深圳市优秀青年基金等各类项目十余项。已发表SCI/EI检索重要期刊及顶级会议论文240余篇，其中SCI检索期刊论文130余篇，谷歌学术总引用超5000次，H-Index=37，ESI高被引论文4篇，在斯普林格出版社完成编/专著5部，电子版均列斯普林格出版社下载量Top25%。研究成果获省部级奖励7项，其中一等奖2项。目前已转化知识产权50余项，高价值评估25项，专利贯标10余项，组建4个与企业共建的联合实验室和产业创新中心，已形成理论基础研究+应用基础研究+前沿技术开发+产业技术孵化的全生命周期研发技术模式。
学习经历：
2013-02--2017-07 贝尔法斯特女王大学 博士
2010-09--2013-01 上海大学 硕士
2006-09--2010-07 上海大学 学士
工作经历：
2017-09~现在,中国科学院深圳先进技术研究院, 历任助理研究员，高级工程师，副研究员
2019-04~2019-08,卡迪夫大学, 博士后访问学者
2016-09~2017-02,贝尔法斯特女王大学, 博士后
国际影响力
2022/2023连续两年入选全球前2%顶尖科学家榜单，在10余个学术组织任职，包括4个国际组织会员/高级会员，7个国内一级学会和二级分会理事/委员，4个先进院企业联合中心/平台主任。任3个高水平国际期刊副主编和编委，13次在高水平国际期刊和国内核心期刊组织专刊并任客座主编，主要包括:作为联合创始人共同组建深圳市智能建造产业联盟并任监事长，中国人工智能学会会刊 CAAI Trans on Intelligence Technology(中科院2区)副主编，国际知名期刊Frontiers in Energy Research 副主编(JCR 2区)，国际期刊Complexity(JCR 2区)编委，在中科院一区期刊 Renewable and Sustainable Energy Reviews(中科院1区，影响因子15.9)等8个国际期刊组织专刊; 在国际顶级低碳学科会议IEEE-ISGT，智能计算会议IEEE-WCCI/CEC等30多个国际重要会议任出版主席、专题主席程序委员会委员等; 任2020亚洲人工智能技术大会IPC主席，英国控制大会UKACC2016、系统仿真与可持续能源会议2017、2019等大会秘书长，受邀在IEEE CoEEPE 2022,IEEE-ISGT2018等会议做大会报告和特邀报告20余次。
所获荣誉
1. CIC国际智能建造创新奖, 二等奖, 其他, 2022
2. 中国仿真学会技术创新奖, 一等奖, 部委级, 2022
3. 中国机械工业学会科技进步奖, 二等奖, 部委级, 2021
4. 中国商业联合会科技进步奖, 三等奖, 部委级, 2021
5. 中国自动化学会科技进步奖, 二等奖, 部委级, 2021
6. 中国仪器仪表学会科技进步奖, 三等奖, 部委级, 2021
7. 中国产学研创新促进会科技进步奖, 一等奖, 部委级, 2020
8. 《发电技术》优秀论文奖, 一等奖, 其他, 2019
9. 斯普林格自然中国新发展奖, 一等奖, 其他, 2019
10. 中国电机工程学会优秀论文奖, 三等奖, 其他, 2018
11. 《Journal of Modern Power Systems and Clean Energy》最高引用奖, 一等奖, 其他, 2017
12. 2014生命系统建模仿真及可持续能源与环境大会最佳论文奖, 一等奖, 其他, 2014
科研成果
承担项目
1. 深圳市优秀青年科学基金, 负责人, 地方任务, 2023-01--2026-12
2. 面向能源车联网的电动汽车用能负荷精准感知与能源互联协同调控研究, 负责人, 国家任务, 2021-01--2024-12
3. 电动汽车集群接入下的电力系统主动重调度研究, 负责人, 国家任务, 2021-01--2023-12
4. 青年创新促进会会员, 负责人, 中国科学院计划, 2021-01--2024-12
5. 中科院深圳先进院优秀青年基金项目, 负责人, 研究所自主部署, 2018-10--2020-10
6. 中国博士后基金会面上项目：一等资助, 负责人, 国家任务, 2018-05--2019-12
7. 广东省自然科学基金, 负责人, 地方任务, 2018-10--2021-10
8. 中科院先进院-国信科技人工智能联合实验室, 负责人, 境内委托项目, 2019-10--2022-10
9. 南方新兴超大城市公共安全风险防控系统研发与应用示范, 参与, 国家任务, 2020-01--2022-08
10. 广东省国际合作项目, 参与, 地方任务, 2019-01--2021-12
代表论文
1. Lu Zhang, Yi Feng, Qinge Xiao, Yunlang Xu, Di Li, Dongsheng Yang, Zhile Yang*. Deep reinforcement learning for dynamic flexible job shop scheduling problem considering variable processing times. Journal of Manufacturing Systems, 2023, 71: 257-273.
2. Wenqiang Yang, Xinxin Zhu, Qinge Xiao, Zhile Yang*. Enhanced multi-objective marine predator algorithm for dynamic economic-grid fluctuation dispatch with plug-in electric vehicles. Energy, 2023, 282: 128901.
3. Zhou Wu, Shaoxiong Zeng, Ruiqi Jiang, Haoran Zhang, Zhile Yang. Explainable temporal dependence in multi-step wind power forecast via decomposition based chain echo state networks. Energy, 2023, 270: 126906.
4. Chengke Wu, Xiao Li, Rui Jiang, Yuanjun Guo, Jun Wang, Zhile Yang*. Graph‐based deep learning model for knowledge base completion in constraint management of construction projects. Computer‐Aided Civil and Infrastructure Engineering, 2023, 38(6): 702-719.
5. Meng Yang, Chengke Wu, Yuanjun Guo, Rui Jiang, Feixiang Zhou, Jianlin Zhang, Zhile Yang*. Transformer-based deep learning model and video dataset for unsafe action identification in construction projects. Automation in Construction, 2023, 146: 104703.
6. Zhile Yang, Tianyu Hu, Juncheng Zhu, Wenlong Shang, Yuanjun Guo, Aoife Foley. Hierarchical High-Resolution Load Forecasting for Electric Vehicle Charging: A Deep Learning Approach. IEEE Journal of Emerging and Selected Topics in Industrial Electronics, 2022, 4(1): 118-127.
7. Xiangfei Liu, Mifeng Ren, Zhile Yang*, Gaowei Yan, Yuanjun Guo, Lan Cheng, Chengke Wu. A multi-step predictive deep reinforcement learning algorithm for HVAC control systems in smart buildings. Energy, 2022, 259: 124857.
8. Ping Shao, Zhile Yang*, Yuanjun Guo, Shihao Zhao, Xiaodong Zhu. Multi-objective optimal scheduling of reserve capacity of electric vehicles based on user wishes. Frontiers in Energy Research, 2022, 10: 977013.
9. Wenqiang Yang, Jinzhe Su, Yunhang Yao, Zhile Yang*, Ying Yuan. A novel hybrid whale optimization algorithm for flexible job-shop scheduling problem. Machines, 2022, 10(8): 618.
10. Shihao Zhao, Kang Li, Zhile Yang*, Xinzhi Xu, Ning Zhang. A new power system active rescheduling method considering the dispatchable plug-in electric vehicles and intermittent renewable energies. Applied Energy, 2022, 314: 118715.
11. Guolian Hou, Lijuan Gong, Mengyi Wang, Xiaodong Yu, Zhile Yang*, Xiaolin Mou. A novel linear active disturbance rejection controller for main steam temperature control based on the simultaneous heat transfer search[J]. ISA transactions, 2022, 122: 357-370.
12. Dongsheng Yang, Mingliang Wu, Di Li, Yunlang Xu, Xianyu Zhou, Zhile Yang*. Dynamic opposite learning enhanced dragonfly algorithm for solving large-scale flexible job shop scheduling problem. Knowledge-Based Systems, 2022, 238: 107815.
13. Chengke Wu, Xiao Li, Yuanjun Guo, Jun Wang, Zengle Ren, Meng Wang, Zhile Yang*. Natural language processing for smart construction: Current status and future directions. Automation in Construction, 2022, 134: 104059.
14. Wenqiang Yang, Zhile Yang*, Yonggang Chen, Zhanlei Peng. Modified Whale Optimization Algorithm for Multi-Type Combine Harvesters Scheduling. Machines, 2022, 10(1): 64.
15. Xiaodong Zhu, Shihao Zhao, Zhile Yang*, Ning Zhang, Xinzhi Xu. A parallel meta-heuristic method for solving large scale unit commitment considering the integration of new energy sectors. Energy, 2022, 238: 121829.
16. Mifeng Ren, Xiangfei Liu, Zhile Yang*, Jianhua Zhang, Yuanjun Guo, Yanbing Jia. A novel forecasting based scheduling method for household energy management system based on deep reinforcement learning[J]. Sustainable Cities and Society, 2022, 76: 103207.
17. Mingliang Wu, Dongsheng Yang, Bowen Zhou, Zhile Yang*, Tianyi Liu, Ligang Li, Zhongfeng Wang, Kunyuan Hu. Adaptive population nsga-iii with dual control strategy for flexible job shop scheduling problem with the consideration of energy consumption and weight. Machines, 2021, 9(12): 344.
18. Zhou Wu, Gan Luo, Zhile Yang*, Yuanjun Guo, Kang Li, Yusheng Xue. A comprehensive review on deep learning approaches in wind forecasting applications. CAAI Transactions on Intelligence Technology, 2021.
19. Wenqiang Yang, Zhanlei Peng, Zhile Yang*, Yuanjun Guo, Xu Chen. An enhanced exploratory whale optimization algorithm for dynamic economic dispatch. Energy Reports, 2021, 7: 7015-7029.
20. L. Zhang, T. Hu, Z. Yang*, D. Yang, J. Zhang, Elite and dynamic opposite learning enhanced sine cosine algorithm for application to plat-fin heat exchangers design problem, Neural Computing and Applications, 2021: 1-14.
21. Yuanjun Guo, Zhile Yang*, Kailong Liu, Yanhui Zhang, Wei Feng. A compact and optimized neural network approach for battery state-of-charge estimation of energy storage system. Energy, 2021, 219: 119529.
22. Wenqiang Yang, Tingli Cheng, Yuanjun Guo, Zhile Yang*, Wei Feng. A Modified Social Spider Optimization for Economic Dispatch with Valve-Point Effects. Complexity, 2020
23. Xiaolin Mou, Daniel T. Gladwin, Rui Zhao, Hongjian Sun, Zhile Yang*. Coil Design for Wireless Vehicle-to-Vehicle Charging Systems. IEEE Access, 2020, 8: 172723-172733
24. G. Hou, L. Gong, Z. Yang*, J. Zhang, Multi-objective economic model predictive control for gas turbine system based on quantum simultaneous whale optimization algorithm, Energy Conversion and Management, 2020, 207: 112498
25. Dongsheng Yang, Xianyu Zhou, Zhile Yang*, Yuanjun Guo, Qun Niu. Low Carbon Multi-Objective Unit Commitment Integrating Renewable Generations. IEEE Access, 2020, 8: 207768-207778
26. Li Zhang, Kang Li, Dajun Du, Yuanjun Guo, Minrui Fei, Zhile Yang*. A Sparse Learning Machine for Real-Time SOC Estimation of Li-ion Batteries. IEEE Access, 2020, 8: 156165-156176.
27. Z. Yang, K. Li, Y. Guo, S. Feng, Q. Niu, Y. Xue, A. Foley, A binary symmetric based hybrid meta-heuristic method for solving mixed integer unit commitment problem integrating with significant plug-in electric vehicles, Energy , 2019, 170: 889-905;
28. Z. Yang, K. Liu, J. Fan, Y. Guo, Q. Niu, J. Zhang, A Novel Binary/Real-valued Pigeon Inspired Optimization for Economic/Environment Unit Commitment with Renewables and Plug-in Vehicles, Science China-Information Science (中国科学-信息科学), 2019, 62: 070213;
29. Zhile Yang, Monjur Mourshed, Kailong Liu, Xinzhi Xu, Shengzhong Feng. A novel competitive swarm optimized RBF neural network model for short-term solar power generation forecasting. Neurocomputing, 2020, 397: 415-421
30. 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;
31. Y. Wang, Z. Yang*, M. Mourshed, Y. Guo, Q. Niu, X. Zhu, Demand side management of plug-in electric vehicles and coordinated unit commitment: A novel parallel competitive swarm optimization method, Energy Conversion and Management, 2019, 196,: 935-949;
32. J. Zhu, Z. Yang*, Y. Guo, J. Zhang, H. Yang, Short-term Load Forecasting for Electric Vehicle Charging Stations Based on Deep Learning Approaches, Applied Sciences, 2019, 9(9), 1723;
33. 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;
34. K. Liu, X. Hu, Z. Yang*, Y. Xie, S. Feng, Lithium-ion battery charging management considering the economic costs of electricity-loss and battery degradation, Energy Conversion and Management, 2019, 195: 167-179;
35. Z. Yang, K. Li, Y. Guo, H. Ma, M. Zheng, Compact Real-valued Teaching-Learning Based Optimization with the Applications to Neural Network Training, Knowledge-Based Systems, 2018, 159: 51-62;
36. H. Ma, Z. Yang*, P. You, M. Fei, Multi-objective Biogeography-based Optimization for Dynamic Economic Emission Load Dispatch Considering Plug-in Electric Vehicles Charging, Energy, 2017, Vol. 135:101-111;
37. Z. Yang, K. Li, Q. Niu, Y. Xue, A novel parallel-series hybrid meta-heuristic method for solving a hybrid unit commitment problem, Knowledge-Based Systems, 2017, 134:13-30;
38. Z. Yang, K. Li, Q. Niu, Y. Xue, A comprehensive study of economic unit commitment of power systems integrating various renewable generations and plug-in electric vehicles, Energy Conversion and Management, 2017, 132: 460-481;
39. Z. Yang, K. Li, A. Foley, Computational Scheduling Methods for Integrating Plug-in Electric Vehicles in the Power System: A Review, Renewable and Sustainable Energy Reviews, 2015, 51: 396-416.;
40. Z. Yang, K. Li, Q. Niu, Y. Xue, A. Foley. A Self-Learning Teaching-Learning Based Optimization for Dynamic Economic/Environmental Dispatch Considering Multiple Plug-in Electric Vehicle Loads. Journal of Modern Power System and Clean Energy, 2014, 2(4): 298-307; (Most citation award)
41. W. Liu, Z. Yang*, Kexin Bi, Forecasting the Acquisition of University Spin-outs: An RBF Neural Network Approach, Complexity, 2017;
42. C. Li, H. Wu, Z. Yang*, Y. Wang, Z. Sun, SHLNN based Robust Control and Tracking for Hypersonic Vehicle under Parameter Uncertainty, Complexity, 2017;
43. 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;
44. 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 multi-objective optimization algorithms in power and energy systems, Journal of Zhengzhou University, 2019.09 (In Chinese);
45. 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 865-869
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 865-869 (In Chinese)
46. 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
发表著作
1. Control and Optimization for Integration of Plug-in Vehicles in Smart Grid, IET, 2017-01
2. Advanced Computational Methods in Energy, Power, Electric Vehicles and Their Integrations, Springer, 2017-08
3. Intelligent Computing and Internet of Things, Springer, 2018-08
4. Advances in Green Energy Systems and Smart Grid, Springer, 2018-08
