检索结果-内蒙古大学图书馆

RadarVerses in Metaverses: A CPSI-Based Architecture for 6S Radar systems in CPSS

IEEE TRANSACTIONS ON systemS MAN CYBERNETICS-systemS 2023年第4期53卷 2128-2137页

作者： Liu, Yuhang Shen, Yu Tian, Yonglin Ai, Yunfeng Tian, Bin Wu, Er Chen, Long Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China North Automat Control Technol Inst Lab Parallel Intelligence Taiyuan 030006 Peoples R China

Metaverses have caused significant changes in the industry and their academic foundation can be traced back to the term cyber-physical-social systems (CPSS), which was proposed in 2010. Radar is an important sensor in sensing systems that are widely applied in many fields, especially, in autonomous driving. To deal with the complex environment, smart radars with real-time information processing capabilities are required. Human factors play a critical role in the operation and management of radar systems, thus, digital twins' radars in cyber-physical systems (CPS) are unable to achieve intelligence in CPSS due to an incomplete consideration of human involvement. For this consideration, we propose a novel framework of RadarVerses for smart radars in metaverses based on ACP-based parallel intelligence, which is also known as cyber-physical-social intelligence (CPSI). RadarVerses consist of five main parts which are physical radars, descriptive radars, predictive radars, prescriptive radars, and deep radars. To construct RadarVerses at the technical level, we introduce four main technical foundations: 1) communication technology;2) scenarios engineering;3) foundation models;and 4) digital workers. In addition, we also provide a case study about LiDARs' predictive maintenance of accumulated snow in RadarVerses.

关键词： Cyber-physical-social systems (CPSS) meta-verses parallel intelligence RadarVerses

来源：评论

学校读者我要写书评

暂无评论

Editorial: Robotic intelligence and automation

ROBOTIC INTELLIGENCE AND AUTOMATION

引用

ROBOTIC INTELLIGENCE AND AUTOMATION 2023年第1期43卷 1-2页

作者： Qiao, Hong Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China CAS Ctr Excellence Brain Sci & Intelligence Techno Shanghai Peoples R China

来源：评论

学校读者我要写书评

暂无评论

Foundation Vehicles: From Foundation Intelligence to Foundation Transportation for Future Mobility

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES

引用

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2023年第10期8卷 4287-4291页

作者： Wang, Fei-Yue Lv, Chen Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Nanyang Technol Univ Sch Mech & Aerosp Engn Singapore 639798 Singapore

IEEE TIV has received its 3251 manuscript submissions, which is nearly twice as many as that of last year, 236 submissions are still being reviewed in our system, and 18 are overdue for review scoring. I would like to express my sincere gratitude to all authors, reviewers, and editorial board members for your invaluable contributions and unwavering support. Your dedication has been instrumental in maintaining the high quality and great service of our journal and fostering a vibrant scholarly community [1], [2], [3], [4], [5], [6], [7].

关键词：

来源：评论

学校读者我要写书评

暂无评论

Efficiency Evaluation of Insurance Companies From Multiperiod Perspective

引用

IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL systemS 2024年第2期11卷 2656-2674页

作者： Xie, Qiwei Zhao, Mengfan Li, Rong Li, Wen Zheng, Xiaolong Li, Yongjun Qin, Rui Wang, Xiaojiong Wang, Fei-Yue Beijing Univ Technol Res Base Beijing Modern Mfg Dev Beijing 100124 Peoples R China Hubei Univ Fac Math & Stat Wuhan 430062 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100190 Peoples R China Univ Sci & Technol China Sch Management Hefei 230026 Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Multimodal Artificial Intelligence S Beijing 100190 Peoples R China Chinese Acad Sci Inst Sci & Dev Beijing 100190 Peoples R China

The insurance industry plays a crucial role of the national financial system, and the operating efficiency of insurance companies has always been a significant subject of academic research. This study proposes a multiperiod DEA model to dynamically evaluate the operating efficiency of insurance companies, which not only overcomes the defect of the traditional DEA method ignoring the internal structure of decision-making units, but also extends the limitation of the leader-follower model in evaluating single-period efficiency. By analyzing the efficiency of seven listed insurance companies in China from 2009 to 2018, the following conclusions are drawn. The multiperiod DEA model demonstrates advantages over the leader-follower model. The profitability of insurance companies during the first five years is higher compared with the last five years. There is a significant correlation between premium financing efficiency and overall efficiency. Throughout both periods, the loss ratio, loss reserve ratio, and consumer price index (CPI) are always positively correlated with the efficiency of the insurer, while the gearing ratio is negatively related to the efficiency of the insurer. The correlation among gross domestic product (GDP), total insurance value, tradable financial assets, and corporate efficiency varies over time.

关键词： DEA insurance companies leader-follower model multiple periods

来源：评论

学校读者我要写书评

暂无评论

Sociolinguistic Radar of Phonological Variation and Social Meaning: Variables, Quantitative Methods, and Prospects

引用

IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL systemS 2024年第6期11卷 7734-7741页

作者： Wang, Wei Fan, Lili Wang, Yutong Ni, Qinghua Wang, Fei-Yue Beijing Jiaotong Univ Sch Languages & Commun Studies Beijing 100089 Peoples R China Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Macau Univ Sci & Technol Fac Innovat Engn Macau 999078 Peoples R China Chinese Acad Sci State Key SLab Management & Control Complex Syst Beijing 100190 Peoples R China Macau Univ Sci & Technol Fac Innovat Engn Macau 999078 Peoples R China

Inspired by the term "social radar," which collects and processes information about social behaviors, this article proposed "sociolinguistic radar," which represents an emerging branch in social investigation and evaluation system aiming to explore the dynamic correlation between sociophonetic variants and macrosociological categories, such as age, gender, ethnicity, and socioeconomic status. The classic quantitative methods in this field include sociolinguistic surveys and interview, quantitative sociophonetics, and social network analysis. These methods have been proved to be effective in tracking the cognitive correlates of phonological variables. Under the emerging framework of sociolinguistic radar, speakers are no longer passive carriers, but active agents in transforming linguistic styles in the process of forming social differentiations, thus contributing to the construction of new social meaning. With the advancement in neuroscience and artificial intelligence (AI), the neurosociolinguistic and AI-based sociolinguistic radar research will thrive and empower the scope and strength of detecting linguistic variation. The working mechanism of this emerging model leverages neural and AI tool packages to radar and analyze linguistic variation, communication patterns, and diverse sociolinguistic phenomena. This interdisciplinary approach combines the principles of sociolinguistics, which will thoroughly examine the relationship between language and society.

关键词： Linguistics Radar Social networking (online) Interviews Surveys Radar tracking systematics Artificial intelligence (AI)-based sociolinguistics linguistic variation neurosociolinguistics phonological variables social stratifications sociolinguistic radar sociophonetic variants

来源：评论

学校读者我要写书评

暂无评论

A Data-Driven Iterative Learning Approach for Optimizing the Train control Strategy

引用

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2023年第7期19卷 7885-7893页

作者： Su, Shuai Zhu, Qingyang Liu, Junqing Tang, Tao Wei, Qinglai Cao, Yuan Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China Beijing Jiaotong Univ Frontiers Sci Ctr Smart High speed Railway Syst Beijing 100044 Peoples R China Univ Chinese Acad Sci Inst Automat Chinese Acad Sci Sch Artificial IntelligenceKey Lab Management & C Beijing 100049 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100049 Peoples R China

The energy-efficient train control (EETC) problem is investigated in this article. And a soft actor-critic (SAC)-based method is proposed to optimize the train driving strategy. First, EETC problem is converted to the inverse problem, i.e., minimizing the trip time of the journey with constant energy consumption. Based on the conversion, the EETC problem is reformulated as a finite Markov decision process, which can be solved by deep reinforcement learning algorithms. Second, an optimization method based on the SAC method is designed to calculate the optimal driving strategy of the train with introducing the reservoir sampling method. Finally, some case studies are conducted to verify the effectiveness and performance of the proposed method. Simulation results demonstrate that a good energy-saving performance can be achieved. In single interval, the SAC-based method can reduce about 1.65% of the energy consumption compared with numerical method. And the energy consumption reduction can be extended to be 6.49% when the proposed approach is applied in multiple intervals.

关键词： Deep reinforcement learning (RL) driving strategy energy-efficient train control (EETC) soft actorcritic (SAC)

来源：评论

学校读者我要写书评

暂无评论

Event-Triggered Parallel control Using Deep Reinforcement Learning With Application to Comfortable Autonomous Driving

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES

引用

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2024年第3期9卷 4470-4479页

作者： Lu, Jingwei Li, Lefei Wang, Fei-Yue Tsinghua Univ Dept Ind Engn Beijing 100084 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Macau Univ Sci & Technol Fac Innovat Engn Macau 999078 Peoples R China

A novel event-triggered control (ETC) method, called deep event-triggered parallel control (deep-ETPC), is presented to achieve path tracking for comfortable autonomous driving (CAD) using parallel control and deep deterministic policy gradient (DDPG). Based on parallel control, the developed deep-ETPC method constructs a dynamic control policy by introducing variation rates of controls. By employing variation rates of controls, the developed deep-ETPC method is capable of indicating communication loss and comfortable driving indices in the reward, and then enables reinforcement learning (RL) agents to learn comfortable ETC driving policies directly. Moreover, the communication loss, which reflects ETC, is integrated into the reward, so there is no need to additionally design/train triggering conditions, which can be considered a type of multi-tasking learning. Furthermore, an ETPC-oriented DDPG algorithm is developed to achieve the developed deep-ETPC method, making DDPG applicable to ETC. Empirical results, including tracking a simple straight line trajectory and a complicated sinusoidal trajectory, demonstrate the effectiveness of the developed deep-ETPC method.

关键词： Autonomous driving comfort driving deep deterministic policy gradient (DDPG) event-triggered control (ETC) parallel control

来源：评论

学校读者我要写书评

暂无评论

Guest Editorial: Cyber-Physical-Social Intelligence: Toward Metaverse-Based Smart Societies of 6I and 6S

引用

IEEE TRANSACTIONS ON systemS MAN CYBERNETICS-systemS 2023年第4期53卷 2018-2024页

作者： Wang, Fei-Yue Tang, Ying Werbos, Paul J. Chinese Acad Sci State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Rowan Univ Dept Elect & Comp Engn Glassboro NJ 08028 USA Missouri Univ Sci & Technol Rolla MO 65409 USA

Transformational development in science and engineering rapidly integrates machine intelligence and human intelligence to form cyber-physical-social intelligence (CPSI), underpinning the growing interactions of cyberspace, physical space, and social space. A multidimensional reality is emerging and evolving with these interactions, leading to the creation of many new concepts and frameworks, such as parallel intelligence, digital twin, and metaverse. Meanwhile, new challenges continue to arise when we seek to reveal the fundamental principles for command and control of the new and extended reality by identifying and characterizing the relations of machines, humans, and nature. To meet these challenges, it is important for us to understand and explore algorithmic theories and processes that constitute CPSI, and to build cyber-physical-social systems (CPSS) [1] with the features of agility, focus, and convergence that are vital to ensure an inclusive, sustainable, equitable, and resilient future for people and our planet.

关键词： Special issues and sections Cyber-physical systems Metaverse Machine intelligence Human intelligence Extended reality Digital twins Cyberspace Command and control systems

来源：评论

学校读者我要写书评

暂无评论

The Milestones of IEEE TIV: The Best Associate Editors and George N. Saridis Best Papers Awards

引用

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2022年第4期7卷 801-803页

作者： Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

Presents the recipients of ITSS society awards.

关键词： Awards

来源：评论

学校读者我要写书评

暂无评论

Logistics 5.0: From Intelligent Networks to Sustainable Ecosystems

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES

引用

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2023年第7期8卷 3771-3774页

作者： Li, Juanjuan Qin, Rui Olaverri-Monreal, Cristina Prodan, Radu Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Multimodal Artificial Intelligence S Beijing 100190 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Johannes Kepler Univ Linz Chair Sustainable Transport Logist 4 0 A-4040 Linz Austria Univ Klagenfurt Inst Informat Technol A-9020 Klagenfurt Austria Chinese Acad Sci State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Macau Univ Sci & Technol Macao Inst Syst Engn Macau 999078 Peoples R China

As part of TIV's DHW on Vehicle 5.0, this letter introduces a novel concept, Logistics 5.0, to address high complexities in logistics Cyber-Physical-Social systems (CPSS). Building upon the theory of parallel intelligence and leveraging advanced technologies and methods such as blockchain, scenarios engineering, Decentralized Autonomous Organizations and Operations (DAOs), Logistics 5.0 promises to accelerate the paradigm shift towards intelligent and sustainable logistics. First, the parallel logistics framework is proposed, and the logistics ecosystem is discussed. Then, the human-oriented operating systems (HOOS) are suggested to providing intelligent Logistics 5.0 solutions. Logistics 5.0 serves as a critical catalyst in realizing the "6S" objectives, i.e. Safety, Security, Sustainability, Sensitivity, Service, and Smartness, within the logistics industry.

关键词： Cyber-physical-social systems decentralized autonomous organizations and operations human-oriented operating systems Logistics 5.0 parallel logistics

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：