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Networked Knowledge and Complex Networks:An Engineering View 被引量:2
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作者 jinhu lü Guanghui Wen +2 位作者 Ruqian lu Yong Wang Songmao Zhang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2022年第8期1366-1383,共18页
Along with the development of information technologies such as mobile Internet,information acquisition technology,cloud computing and big data technology,the traditional knowledge engineering and knowledge-based softw... Along with the development of information technologies such as mobile Internet,information acquisition technology,cloud computing and big data technology,the traditional knowledge engineering and knowledge-based software engineering have undergone fundamental changes where the network plays an increasingly important role.Within this context,it is required to develop new methodologies as well as technical tools for network-based knowledge representation,knowledge services and knowledge engineering.Obviously,the term“network”has different meanings in different scenarios.Meanwhile,some breakthroughs in several bottleneck problems of complex networks promote the developments of the new methodologies and technical tools for network-based knowledge representation,knowledge services and knowledge engineering.This paper first reviews some recent advances on complex networks,and then,in conjunction with knowledge graph,proposes a framework of networked knowledge which models knowledge and its relationships with the perspective of complex networks.For the unique advantages of deep learning in acquiring and processing knowledge,this paper reviews its development and emphasizes the role that it played in the development of knowledge engineering.Finally,some challenges and further trends are discussed. 展开更多
关键词 Complex network knowledge graph networked knowledge neural network
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Bridging the gap between complex networks and smart grids 被引量:3
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作者 Wenwu Yu Guanghui Wen +2 位作者 Xinghuo Yu Zaijun Wu jinhu lü 《Journal of Control and Decision》 EI 2014年第1期102-114,共13页
It is well known that many real-world systems can be described by complex networks with the nodes and the edges representing the individuals and their communications,respectively.Based on recent advances in complex ne... It is well known that many real-world systems can be described by complex networks with the nodes and the edges representing the individuals and their communications,respectively.Based on recent advances in complex networks,this paper aims to provide some new methodologies to study some fundamental problems in smart grids.In particular,it summarises some results for network properties,distributed control and optimisation,and pinning control in complex networks and tries to reveal how these new technologies can be applied in smart grids. 展开更多
关键词 smart grids complex networks CONSENSUS multi-agent systems distributed control and optimisation pinning control
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精准智能理论:面向复杂动态对象的人工智能 被引量:16
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作者 郑志明 吕金虎 +1 位作者 韦卫 唐绍婷 《中国科学:信息科学》 CSCD 北大核心 2021年第4期678-690,共13页
新一轮科技革命和产业变革正在萌发,以深度学习和大数据为基础,以Alpha Go等为典型应用场景掀起了人工智能的第3次高潮.传统的基于统计线性化动态建模的人工智能,在处理复杂对象时遇到了可解释性、泛化性和可复现性等发展瓶颈,迫切需要... 新一轮科技革命和产业变革正在萌发,以深度学习和大数据为基础,以Alpha Go等为典型应用场景掀起了人工智能的第3次高潮.传统的基于统计线性化动态建模的人工智能,在处理复杂对象时遇到了可解释性、泛化性和可复现性等发展瓶颈,迫切需要建立基于复杂性与多尺度分析的新一代人工智能理论,我们称之为精准智能.针对复杂系统的非线性特征,精准智能构建内嵌领域知识和数学物理机理的系统学习理论,包括复杂数据科学感知、复杂系统精准构建、复杂行为智能分析3个层次.具体而言,通过复杂数据科学感知建立内嵌时空特征与数理规律等具有可解释性的科学数据系统;通过复杂系统精准构建反演具有非线性复杂逻辑关系的多层次、多尺度、可解释的人工智能动态学习模型;通过对系统复杂行为智能分析建立面向系统行为演进和全局动态分析的可解释可调控人工智能新理论和新方法.将上述精准智能理论应用于群体智能,提出了群体熵方法,实现了群体激发和汇聚行为复杂性度量与有效引导调控. 展开更多
关键词 人工智能 可解释性 非线性 复杂性 精准智能
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