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平行系统和数字孪生的一种数据驱动形式表示及计算框架

张俊 许沛东 王飞跃

张俊, 许沛东, 王飞跃. 平行系统和数字孪生的一种数据驱动形式表示及计算框架. 自动化学报, 2020, 46(7): 1346-1356. doi: 10.16383/j.aas.c200347
引用本文: 张俊, 许沛东, 王飞跃. 平行系统和数字孪生的一种数据驱动形式表示及计算框架. 自动化学报, 2020, 46(7): 1346-1356. doi: 10.16383/j.aas.c200347
ZHANG Jun, XU Pei-Dong, WANG Fei-Yue. Parallel Systems and Digital Twins: A Data-driven Mathematical Representation and Computational Framework. ACTA AUTOMATICA SINICA, 2020, 46(7): 1346-1356. doi: 10.16383/j.aas.c200347
Citation: ZHANG Jun, XU Pei-Dong, WANG Fei-Yue. Parallel Systems and Digital Twins: A Data-driven Mathematical Representation and Computational Framework. ACTA AUTOMATICA SINICA, 2020, 46(7): 1346-1356. doi: 10.16383/j.aas.c200347

平行系统和数字孪生的一种数据驱动形式表示及计算框架

doi: 10.16383/j.aas.c200347
基金项目: 

国家重点研发计划 2018AAA0101504

详细信息
    作者简介:

    张俊  武汉大学电气与自动化学院教授. 2003年和2005年分别获得华中科技大学电子信息与通信工程系学士与硕士学位. 2008年获得亚利桑那州立大学电气工程博士学位.主要研究方向为智能系统, 人工智能, 知识自动化, 及其在智能电力和能源系统中的应用. E-mail: jun.zhang.ee@whu.edu.cn

    许沛东  武汉大学电气与自动化学院博士研究生. 2018年获得武汉大学电气工程学院硕士学位.主要研究方向为人工智能, 智能电网. E-mail: xupd@whu.edu.cn

    通讯作者:

    王飞跃  中国科学院自动化研究所复杂系统管理与控制国家重点实验室主任, 中国科学院大学中国经济与社会安全研究中心主任, 青岛智能产业技术研究院院长.主要研究方向为平行系统的方法与应用, 社会计算, 平行智能以及知识自动化.本文通信作者. E-mail: feiyue.wang@ia.ac.cn

Parallel Systems and Digital Twins: A Data-driven Mathematical Representation and Computational Framework

Funds: 

National Key R & D Program of China 2018AAA0101504

More Information
    Author Bio:

    ZHANG Jun   Professor at the School of Electrical Engineering and Automation, Wuhan University. He received his bachelor and master degrees in electrical engineering from Huazhong University of Science and Technology, Wuhan, China, in 2003 and 2005, respectively, and his Ph. D. degree in electrical engineering from Arizona State University, USA, in 2008. His research interest covers intelligent systems, artificial intelligence, knowledge automation, and their applications in intelligent power and energy systems

    XU Pei-Dong   Ph. D. candidate at the School of Electrical Engineering and Automation, Wuhan University. He received his master degree from the School of Electrical Engineering, Wuhan University in 2018. His research interest covers artificial intelligence, smart grid

    Corresponding author: WANG Fei-Yue   State specially appointed expert and director of the State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences. Director of China Economic and Social Security Research Center in University of Chinese Academy of Sciences. Dean of Qingdao Academy of Intelligent Industries. His research interest covers methods and applications for parallel systems, social computing, parallel intelligence, and knowledge automation. Corresponding author of this paper
  • 摘要: 旨在为平行系统及ACP方法建立一种数据驱动的数学形式和计算框架, 该形式与框架也适用于数字孪生系统.首先, 基于动态系统状态方程方法论, 给出了平行系统的虚实双系统表示方法, 基于此表示方法为平行系统问题提供了一种数学表示.围绕该表示, 讨论了虚实系统互动、平行系统与数字孪生系统异同等问题.然后, 为ACP方法提供了一种计算框架, 详细解释了人工系统(Artificial systems, A)、计算实验(Computational experiments, C)、平行执行(Parallel execution, P)的数学计算求解过程, 并讨论了“学习与训练”、“实验与评估”、“管理与控制”、灵捷–聚焦–收敛(AFC)、小数据-大数据-小智能等概念的相关数学表示, 并讨论了智能科学与平行系统数学架构的关系以及平行智能的内涵.最后, 以大学校园园区能源管理系统为案例, 为平行系统数学架构和方法提供一个直观的算例.
    Recommended by Associate Editor LIU De-Rong
    1)  本文责任编委  刘德荣
  • 图  1  平行系统理论与ACP方法

    Fig.  1  Parallel system theory and ACP method

    图  2  美国某大学校园电网的网络拓扑

    Fig.  2  The network topology of the campus network of an American university

    图  3  校园能源社区系统管控流程

    Fig.  3  Management and control process of campus energy community system

    图  4  夏季场景中6个目标楼宇的总体社会成本与不同室内温度设置的比较

    Fig.  4  Comparison of the total social cost of six target buildings and different indoor temperature settings in summer

    表  1  用于训练目标建筑物的隐藏神经元的数量和训练结果的回归R值

    Table  1  The number of hidden neurons used to train the target building and the regression R value of training results

    编号 建筑名 隐藏神经元(个) R值
    1 里奇中心 30 0.88
    2 法律大楼 20 0.96
    3 斯特姆礼堂 30 0.96
    4 丹尼尔大楼 30 0.86
    5 纽曼中心 50 0.86
    6 奥林中心 5 0.94
    下载: 导出CSV
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  • 收稿日期:  2020-05-23
  • 录用日期:  2020-07-02
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