Han Shuangshuang
Chinese Academy of Sciences
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Featured researches published by Han Shuangshuang.
Archive | 2018
王飞跃; Wang Feiyue; 孙奇; Sun Qi; 江国进; Jiang Guo-Jin; 谭珂; Tan Ke; 张俊; Zhang Jun; 侯家琛; Hou Jiachen; 熊刚; Xiong Gang; 朱凤华; Zhu Fenghua; 韩双双; Han Shuangshuang; 董西松; Dong Xisong; 王嫘; Wang Lei
本文旨在讨论核能5.0(Nuclear Energy 5.0)的基本概念、体系架构和关键平台技术等问题.首先讨论了核能5.0出现的新智能时代基础,阐述了虚拟数字工业崛起的技术背景.详细叙述了核电工业新形态与体系结构,即平行核能的定义、意义、研究内容、体系架构以及应用领域.接下来讨论了核能5.0中新一代核心技术,包括核能物联网、知识自动化、发展性人工智能、大规模协同演进技术、核能区块链等.最后讨论了核能5.0中在核电系统的具体应用场景与案例,重点是核电工控系统安全评估与核电站数字化仪控系统.
SCIENTIA SINICA Informationis | 2017
Wang Feiyue; Yang Liuqing; Hu Xiaoya; Cheng Xiang; Han Shuangshuang; Yang Jian
The coexistence of various protocols for current networks leads to extremely complex network systems, which not only limits the development of network technologies, but also cannot meet the growing demands for cloud computing, big data, service visualization applications, etc. With the development of information telecommunication technology, decreasing hardware costs, and the rise of open source packages, network systems have become more dynamic and flexible, and network service providers expect easier access to the information technology market. A new business model and collaborative competition must be formed.However, current network systems are becoming increasingly complex, which also increases project and societal complexity. The attributes of multi-field, dynamicity, and unpredictability lead network systems to be massively complex, making it difficult to comprehensively evaluate and accurately amend their schema. Therefore, as a new network architecture, parallel network is expected to revolutionize the current network situation and meet the evolving demand for network services. The core idea of parallel networking is to construct artificial networks and effectively optimize the network system operations via the interactions between real networks and artificial networks. Through computational experiments and analysis of the artificial networks, a control strategy based on network traffic flow can be continuously tracked and updated in real-time. Meanwhile, the collected operating status of the real network can also be used to optimize the model of the artificial network. These strategies can be applied to all types of network equipment to control network operations. Therefore, it is possible to allocate network resources more effectively, to improve the management and utilization of resources, and to provide new network solutions to address changing network demands more effectively.
Archive | 2014
Qu Fengzhong; Yang Liuqing; Bai Junyan; Zhang Bin; Chen Shichao; Yang Jian; Han Shuangshuang
Archive | 2014
Wang Feiyue; Chen Shichao; Zhu Fenghua; Tian Bin; Yang Liuqing; Xiong Gang; Han Shuangshuang; Huang Wuling
Archive | 2015
Chen Shichao; Han Shuangshuang; Yang Liuqing; Zhu Fenghua; Wang Feiyue
Archive | 2015
Chen Shichao; Han Shuangshuang; Yang Liuqing; Zhu Fenghua; Wang Feiyue
Archive | 2017
Han Shuangshuang; Wang Feiyue; Zhu Fenghua; Wang Yingchun
Archive | 2017
Wang Feiyue; Han Shuangshuang; Wang Yingchun
Archive | 2017
Yang Jian; Han Shuangshuang; Wang Feiyue
Archive | 2017
Wang Yingchun; Yao Tingting; Han Shuangshuang; Cao Dongpu; Wang Feiyue