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Emissions reduction potential and feasibility of vehicle-to-grid for Beijing's future electric vehicles

Cell Reports Physical Science 2025年第6期6卷

作者： Xu, Jiaxin Chen, Jiahui Wei, Hongyi Zhao, Yinan Tian, Bowen Wen, Yifan Jiang, Haiyang Zhang, Ning Zhang, Shaojun Wu, Ye School of Environment Tsinghua University Beijing 100084 China Center for Sustainable Systems School for Environment and Sustainability University of Michigan Ann Arbor 48109 MI United States School of Electrical and Power Engineering Power System Research Institute Tsinghua University Beijing 100084 China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084 China Beijing Laboratory of Environmental Frontier Technologies School of Environment Tsinghua University Beijing 100084 China State Key Laboratory of Regional Environment and Sustainability Tsinghua University Beijing 100084 China

Electric vehicles (EVs) offer significant potential to reduce greenhouse gas (GHG) emissions from road transport. However, nighttime charging increases peak demand and thermal power reliance. This study evaluates vehicle-to-grid (V2G) as a solution by integrating GPS-based EV travel data with hourly grid modeling for 2 million EVs in Beijing. Results show V2G boosts renewable energy use in charging to 66%, up from under 4% in uncoordinated charging. V2G cuts vehicle uncoordinated charging emissions by 20.6% and reduces the grid's GHG footprint by replacing thermal power with discharging electricity. Commuter vehicles and the summer months offer the highest V2G emissions reduction potential. The study finds battery degradation manageable and highlights synergies between V2G, renewable capacity expansion, and economic incentives, while emphasizing the need for robust infrastructure and local grid networks to support large-scale EV adoption. This approach therefore offers a promising pathway to accelerate sustainable energy solutions amid increasing vehicle electrification and renewable integration. © 2025 The Author(s)

关键词： electric vehicles GHG emissions grid optimization travel pattern V2G vehicle to grid

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A Blockchain-based Framework for Central Bank Digital Currency

A Blockchain-based Framework for Central Bank Digital Curren...

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2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019

作者： Han, Xuan Yuan, Yong Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Research Center of Military Computational Experiments and Parallel System National University of Defense Technology Changsha China

ISBN: (纸本)9781728128535

Cryptocurrency and blockchain technologies have developed in parallel in recent years, with technological breakthroughs in currency issuance, payment methods, and currency storage. However, the existing cryptocurrencies cannot replace fiat money. There is a huge gap between decentralized cryptocurrency and central bank digital currency, namely CBDC, in terms of monetary governance and circulation. In this paper, we propose the function and security requirements of CBDC, through a comprehensive analysis of the existing typical cryptocurrency and the prototype of the CBDC scheme. On this basis, we present a blockchain-based framework for CBDC with three layers, including supervisory layer, network layer and user layer, and describe the key business processes of the CBDC's entire lifecycle of issuance-circulation-withdrawal in detail. Finally, we take cross-border payment as an example to explain the transaction process of CBDC. We aim to provide theoretical guidance for CBDC design. © 2019 IEEE.

关键词： Blockchain

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Deep Kalman Filter with Optical Flow for Multiple Object Tracking

Deep Kalman Filter with Optical Flow for Multiple Object Tra...

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IEEE International Conference on systems, Man and Cybernetics

作者： Yaran Chen Dongbin Zhao Haoran Li State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing

Deep matching and Kalman filter-based multiple object tracking (DK-tracking) have been demonstrated to be promising. However, most of existing DK-tracking trackers assume that objects are slow-varying movement with a constant velocity. The assumption is hard to be satisfied in the real world, especially in the image space due to the sight distance. In this paper, we propose a novel multiple object tracking method combining deep feature matching, Kalman filter and flow information, which is called DK-flow-tracking, to improve tracking performance. In DK-flow-tracking, optical flow in consecutive frames is used to provide accurate object motion information for guiding Kalman filter to track objects. Experiments are performed on public datasets: MOT2016, MOT2017, and the proposed method achieves better performances compared to the DK-tracking with the assumption of a constant velocity movement.

关键词： Kalman filters Optical flow Target tracking Feature extraction Object tracking Optical filters

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An Interpretable Neural Network Model Through Piecewise Linear Approximation

arXiv

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arXiv 2020年

作者： Guo, Mengzhuo Zhang, Qingpeng Liao, Xiuwu Zeng, Daniel Dajun School of Management Xi’an Jiaotong University School of Data Science City University of Hong Kong State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Department of Management Information Systems Eller College of Management University of Arizona

Most existing interpretable methods explain a black-box model in a post-hoc manner, which uses simpler models or data analysis techniques to interpret the predictions after the model is learned. However, they (a) may derive contradictory explanations on the same predictions given different methods and data samples, and (b) focus on using simpler models to provide higher descriptive accuracy at the sacrifice of prediction accuracy. To address these issues, we propose a hybrid interpretable model that combines a piecewise linear component and a nonlinear component. The first component describes the explicit feature contributions by piecewise linear approximation to increase the expressiveness of the model. The other component uses a multi-layer perceptron to capture feature interactions and implicit nonlinearity, and increase the prediction performance. Different from the post-hoc approaches, the interpretability is obtained once the model is learned in the form of feature shapes. We also provide a variant to explore higher-order interactions among features to demonstrate that the proposed model is flexible for adaptation. Experiments demonstrate that the proposed model can achieve good interpretability by describing feature shapes while maintaining state-of-the-art accuracy. Copyright © 2020, The Authors. All rights reserved.

关键词： Piecewise linear techniques

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Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveys

arXiv

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arXiv 2023年

作者： Chen, Long Li, Yuchen Huang, Chao Li, Bai Xing, Yang Tian, Daxin Li, Li Hu, Zhongxu Na, Xiaoxiang Li, Zixuan Teng, Siyu Lv, Chen Wang, Jinjun Cao, Dongpu Zheng, Nanning Wang, Fei-Yue The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Waytous Ltd United Kingdom BNU-HKBU United International College Zhuhai519087 China Hong Kong Baptist University Kowloon999077 Hong Kong The Department of Industrial and System Engineering Hong Kong Polytechnical University Hong Kong The College of Mechanical and Vehicle Engineering Hunan University China The School of Aerospace Transport and Manufacturing Cranfield University United Kingdom The School of Transportation Science and Engineering Beihang University China The Department of Automation Tsinghua University China The Department of Mechanical and Aerospace Engineering Nanyang Technological University Singapore The Centre for Sustainable Road Freight University of Cambridge United Kingdom The School of Mechanical Engineering Tsinghua University China The College of Artificial Intelligence Xi’an Jiaotong University China

Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace due to the convenience, safety, and economic benefits. Although a number of surveys have reviewed research achievements in this field, they are still limited in specific tasks, lack of systematic summary and research directions in the future. Here we propose a Survey of Surveys (SoS) for total technologies of AD and IVs that reviews the history, summarizes the milestones, and provides the perspectives, ethics, and future research directions. To our knowledge, this article is the first SoS with milestones in AD and IVs, which constitutes our complete research work together with two other technical surveys. We anticipate that this article will bring novel and diverse insights to researchers and abecedarians, and serve as a bridge between past and future. Copyright © 2023, The Authors. All rights reserved.

关键词： Autonomous vehicles

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Discriminative graph regularized broad learning system for image recognition

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Science China(Information Sciences) 2018年第11期61卷 179-192页

作者： Junwei JIN Zhulin LIU C.L.Philip CHEN Faculty of Science and Technology University of Macau Dalian Maritime University State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

Broad learning system(BLS) has been proposed as an alternative method of deep learning. The architecture of BLS is that the input is randomly mapped into series of feature spaces which form the feature nodes, and the output of the feature nodes are expanded broadly to form the enhancement nodes, and then the output weights of the network can be determined analytically. The most advantage of BLS is that it can be learned incrementally without a retraining process when there comes new input data or neural nodes. It has been proven that BLS can overcome the inadequacies caused by training a large number of parameters in gradient-based deep learning algorithms. In this paper, a novel variant graph regularized broad learning system(GBLS) is proposed. Taking account of the locally invariant property of data, which means the similar images may share similar properties, the manifold learning is incorporated into the objective function of the standard BLS. In GBLS, the output weights are constrained to learn more discriminative information,and the classification ability can be further enhanced. Several experiments are carried out to verify that our proposed GBLS model can outperform the standard BLS. What is more, the GBLS also performs better compared with other state-of-the-art image recognition methods in several image databases.

关键词： broad learning system deep learning graph regularization image recognition feature extraction incremental learning

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Research and practice of lightweight digital twin speeding up the implementation of flexible manufacturing systems

Research and practice of lightweight digital twin speeding u...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Xiaodong Zhang Bin Hu Gang Xiong Xinjie Liu Xisong Dong Dongjia Li School of Information Engineering Yantai institute of Technology Yantai China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Chinese Academy of Sciences Beijing China Yantai University Yantai China School of Artificial Intelligence Yantai Institute of Technology Yantai China

Parallel manufacturing in Industry 5.0 requires digital twin to digitize physical systems, building virtual models to open up channels connecting physical systems, information systems, and social systems, and transforming the physical models of the existing production environment to achieve two-way feedback of virtual and real is the current research direction. This paper proposes the modeling idea of lightweight digital twin, extracts core dimensions and performs digital virtual simulation, so as to quickly realize the complete process of two-way feedback, and realize a set of chess flexible parallel manufacturing production lines as a practice for the design of complete lightweight digital twin.

关键词： Industries Digital twin Conferences Buildings Production Manufacturing Flexible manufacturing systems

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Parameter estimation survey for multi-joint robot dynamic calibration case study

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中国科学:化学（英文版） 2019年第10期62卷 98-112页

作者： Shaolin ZHANG Shuo WANG Fengshui JING Min TAN The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai 200031 China

Accurate model parameters are the basis of robot *** linear and nonlinear models have been proposed to calibrate the inertial parameters and friction parameters of multi-joint ***,methods of choosing a model and calculating its parameters still have few *** paper reviews typical linear/nonlinear models and different calculation methods for robot dynamic *** simulations,the features of different methods are analyzed,including torque error,parameter error,model adaptability,solution time,and anti-interference ability of the calibration ***,an experiment performed on a six-degree-of-freedom industrial manipulator is used as an example to illustrate how to select the model for a specified *** comparisons and experiments provide references for the parameter calibration of multi-joint robots.

关键词： dynamic parameter calibration friction calibration robot dynamics industrial manipulator dynamic models

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Bitcoin exchange addresses identification and its application in online drug trading regulation 2

Bitcoin exchange addresses identification and its applicatio...

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23rd Pacific Asia Conference on Information systems: Secure ICT Platform for the 4th Industrial Revolution, PACIS 2019

作者： Liang, Jiaqi Li, Linjing Luan, Shu Gan, Lu Zeng, Daniel State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Shenzhen China

A typical example of the impact of the use of Bitcoin on smart health is the darknet market, the website for Bitcoin-based drug sales, and the anonymity exacerbates regulatory difficulties. Bitcoin exchanges are critical portals that link the physical world with cyberspace through buying and selling Bitcoins using fiat money, such as USD and Euro. Thus, identifying exchange addresses in the Bitcoin transaction network is the primary step to detect drug trading in darknet markets. In this paper, we first validate that the exchange addresses are identifiable. Then we propose identification methods based on embedding representation of transaction network. Experimental results on a dataset with records of one-week transactions validated the effectiveness of our method. This work will offer the basis for subsequent applications in smart health. © Proceedings of the 23rd Pacific Asia Conference on Information systems: Secure ICT Platform for the 4th Industrial Revolution, PACIS 2019.

关键词： Bitcoin

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Conservative Policy Gradient in Multi-critic Setting

Conservative Policy Gradient in Multi-critic Setting

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Chinese Automation Congress (CAC)

作者： Bao Xi Rui Wang Shuo Wang Tao Lu Yinghao Cai University of Chinese Academy of Sciences Beijing China State Key Laboratory of Management and Control for Complex System Institute of Automation Beijing China

Twin Delayed Deep Deterministic policy gradient algorithm (TD3) addressed the overestimation bias problem by adopting a clipped Double Q-Learning method. As the two Q networks are different, the updation of a policy to maximize one Q function might minimize another, which is called inconsistency in this paper. Therefore, we propose an algorithm based on TD3, conservative policy gradient (CPG), that optimizes the policy with respect to the lower bound of the two Q functions to deal with the inconsistancy. In Q function learning, one-step estimate is usually used in target value estimation. However, due to the constantly changing target networks, there will be fluctuations in the estimation. As the target Q function is changing slowly, we combine the one-step estimate with zero-step estimate to avoid sharp changes. The experimental results illustrate that CPG outperforms TD3 and some other reinforcement learning methods on multiple MuJoCo benchmarks.

关键词： Training Benchmark testing Estimation Learning (artificial intelligence) Games Robots Task analysis

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