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IEEE International Conference on systems, Man and Cybernetics

作者： Xutao Feng Yaofei Ma Liping Zhao Hanbo Yang Beihang University School of Automation Science and Electrical Engineering Beijing China National Key Laboratory of Modeling and Simulation for Complex Systems Beijing Simulation Center Beijing China

A multi-agent decision network based on QMIX is proposed in this paper to cope with the coordination decision problem of multiple UAV air combat missions. To speed up the training process, three improvements are introduced: 1) An improved $\epsilon$ -decaying method that enable some tutor to help in action selection at the early stage of the training. This measure greatly improves the exploring efficiency when the network are far from being fully trained; 2) State pruning and action mask measures are applied during the training. The former improves the effectiveness of the input state information, and the latter reduces unnecessary action exploring. 3) A gradually training configuration is used to make the training process more robust, where the combat adversaries are configured as the static targets, the randomly maneuver vehicles, and the Min-Max strategy vehicles respectively. The multi-UAV air combat scenarios are built up and the experiments are conducted. The results shows that these improvements have significantly improved training efficiency.

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Two improved anisotropic Liouville type theorems for the stationary 3D Navier–Stokes equations

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Archiv der Mathematik 2025年第5期124卷 571-582页

作者： Zhang, Zhibing Zu, Qian School of Mathematics and Physics Key Laboratory of Modeling Simulation and Control of Complex Ecosystem in Dabie Mountains of Anhui Higher Education Institutes Anqing Normal University Anqing 246133 China School of Mathematics and Statistics Anhui Normal University Wuhu 241002 China School of Mathematics and Physics Anqing Normal University Anqing 246133 China

In this paper, we establish two new anisotropic Liouville type theorems for the stationary 3D Navier–Stokes equations. Under certain anisotropic integrability conditions on the components of the velocity, we show that the solution is trivial. Our results extend and improve the results of Chae (Appl Math Lett 142:108655, 2023) and Luo and Yin (Arch Ration Mech Anal 224:209–231, 2017). © Springer Nature Switzerland AG 2025.

关键词： Anisotropic Liouville type theorem Stationary Navier–Stokes equations

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"Why not looking backward?" a robust two-step method to automatically terminate Bayesian optimization 23

"Why not looking backward?" a robust two-step method to auto...

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Proceedings of the 37th International Conference on Neural Information Processing systems

作者： Shuang Li Ke Li Wei Li Control and Simulation Center Harbin Institute of Technology China and National Key Laboratory of Modeling and Simulation for Complex Systems China Department of Computer Science University of Exeter Exeter UK

Bayesian Optimization (BO) is a powerful method for tackling expensive blackbox optimization problems. As a sequential model-based optimization strategy, BO iteratively explores promising solutions until a predetermined budget, either iterations or time, is exhausted. The decision on when to terminate BO significantly influences both the quality of solutions and its computational efficiency. In this paper, we propose a simple, yet theoretically grounded, two-step method for automatically terminating BO. Our core concept is to proactively identify if the search is within a convex region by examining previously observed samples. BO is halted once the local regret within this convex region falls below a predetermined threshold. To enhance numerical stability, we propose an approximation method for calculating the termination indicator by solving a bilevel optimization problem. We conduct extensive empirical studies on diverse benchmark problems, including synthetic functions, reinforcement learning, and hyperparameter optimization. Experimental results demonstrate that our proposed method saves up to ≈ 80% computational budget yet is with an order of magnitude smaller performance degradation, comparing against the other peer methods. In addition, our proposed termination method is robust in terms of the setting of its termination criterion.

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Short-Term Traffic Flow Prediction Method Based on Spatio-Temporal Characteristics of complex Road Network

Short-Term Traffic Flow Prediction Method Based on Spatio-Te...

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2021 International Conference on Applied Mathematics, modeling and Computer simulation, AMMCS 2021

作者： Zhu, Huawei Mao, Yihao Zhao, Yiming Shi, Liyuan Shao, Yanli School of Information and Electrical Engineering Zhejiang University City College Hangzhou310015 China Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China

ISBN: (纸本)9781643682549

With the development of urbanization, the number of residents' motor vehicles has increased sharply, and traffic congestion problem has become increasingly serious. The construction of Intelligent Traffic System (ITS) has become the main means to alleviate traffic congestion. Short-term traffic flow prediction has guiding significance for residents' travel planning and intelligent management of transportation, and has become one of the research hotspots in intelligent transportation ***, A short-term traffic flow prediction method based on the spatio-temporal characteristics of complex road networks is proposed to further improve the prediction accuracy and reduce the prediction cost. Firstly, a graph convolutional network (GCN) capable of processing non-Euclidean data structures is used to extract the spatial characteristics of traffic flow data. Then, the long and short-term memory (LSTM) neural network is used to process the time characteristics. Finally, the two are combined to realize the effective processing of the spatio-temporal characteristics of traffic flow data. Experimental results on the real traffic flow dataset prove the feasibility and effectiveness of the proposed method, and can provide a basis for intelligent traffic control and smart city construction. © 2022 The authors and IOS Press.

关键词： Traffic congestion

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modeling the dynamic alignment of business and information systems via the lens of human-centered architecture evolution

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Journal of systems Engineering and Electronics 2021年第4期32卷 881-888页

作者： ZHANG Mengmeng YI Shuanghui CHEN Honghui LUO Aimin LIU Junxian ZHANG Xiaoxue Science and Technology on Information Systems Engineering Laboratory National University of Defense TechnologyChangsha 410072China National Key Laboratory for Complex System Simulation Military Academy of SciencesBeijing 100080China

The complexity of business and information systems(IS)alignment is a growing concern for researchers and practitioners *** extant research on alignment architecture fails to consider the human viewpoint,which makes it difficult to embrace emergent *** paper contributes to the extant literature in the following ***,we combine an enterprise architecture(EA)framework with a human viewpoint to address alignment issues in the architecture design phase;second,we describe a dynamic alignment model by developing a humancentered meta-model that explains first-and second-order changes and their effects on alignment *** paper provides better support for the theoretical research and the practical application of dynamic alignment.

关键词： business and information systems(IS)alignment human viewpoint enterprise architecture(EA) meta-model dynamic alignment

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Maximization of k-Submodular Function with d-Knapsack Constraints Over Sliding Window

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Tsinghua Science and Technology 2025年第2期30卷 488-498页

作者： Wenqi Wang Yuefang Sun Zhiren Sun Donglei Du Xiaoyan Zhang School of Mathematical Science&Institute of Mathematics Nanjing Normal UniversityNanjing 210023China Key Laboratory of Ministry of Education Numerical Simulation of Large Scale Complex Systems Nanjing 210023China School of Mathematics and Statistics Ningbo UniversityNingbo 315211China Faculty of Management University of New BrunswickFredericton E3B9Y2Canada

Submodular function maximization problem has been extensively studied recently.A natural variant of submodular function is k-submodular function,which has many applications in real life,such as influence maximization and sensor placement *** domain of a k-submodular function has k disjoint subsets,and hence includes submodular function as a special case when k=*** work investigates the k-submodular function maximization problem with d-knapsack constraints over the sliding *** on the smooth histogram technique,we design a deterministic approximation ***,we propose a randomized algorithm to improve the approximation ratio.

关键词： k-submodular function d-knapsack constraints sliding window streaming algorithm approximation algorithm

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Trends and drivers of anthropogenic NOx emissions in China since 2020

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Environmental Science and Ecotechnology 2024年第5期21卷 287-293页

作者： Hui Li Bo Zheng Yu Lei Didier Hauglustaine Cuihong Chen Xin Lin Yi Zhang Qiang Zhang Kebin He Shenzhen Key Laboratory of Ecological Remediation and Carbon Sequestration Institute of Environment and EcologyTsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhen 518055China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084China State Environmental Protection Key Laboratory of Environmental Planning and Policy Simulation and Center of Air Quality Simulation and System Analysis Chinese Academy of Environmental PlanningBeijing 100041China Laboratoire des Sciences du Climat et de l’Environnement LSCE/IPSLCEA-CNRS-UVSQUniversite Paris-SaclayGif-sur-YvetteFrance Center for Satellite Application on Ecology and Environment Ministry of Ecology and Environment of ChinaBeijing 100094China Institute of Future Human Habitats Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhen 518055China Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing 100084China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China

Nitrogen oxides(NOx),significant contributors to air pollution and climate change,form aerosols and ozone in the ***,timely,and transparent information on NOx emissions is essential for decision-making to mitigate both haze and ozone ***,a comprehensive understanding of the trends and drivers behind anthropogenic NOx emissions from Chinadthe world's largest emitterdhas been lacking since 2020 due to delays in emissions *** we show a consistent decline in China's NOx emissions from 2020 to 2022,despite increased fossil fuel consumption,utilizing satellite observations as constraints for NOx emission estimates through atmospheric *** reduction is corroborated by data from two independent spaceborne instruments:the TROPOspheric Monitoring Instrument(TROPOMI)and the Ozone Monitoring Instrument(OMI).Notably,a reduction in transport emissions,largely due to the COVID-19 lockdowns,slightly decreased China's NOx emissions in *** subsequent years,2021 and 2022,reductions in NOx emissions were driven by the industry and transport sectors,influenced by stringent air pollution *** satellite-based inversion system developed in this study represents a significant advancement in the real-time monitoring of regional air pollution emissions from space.

关键词： China's NOx emissions Pollution control Socio-economic drivers Atmospheric inversion

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FedECCR: Federated Learning Method with Encoding Comparison and Classification Rectification 19th

FedECCR: Federated Learning Method with Encoding Comparison...

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19th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2023

作者： Zeng, Yan Zheng, Hui Wang, Xin Zhang, Beibei Zhou, Mingyao Zhang, Jilin Ren, YongJian School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China Key Laboratory for Modeling and Simulation of Complex Systems Ministry of Education Hangzhou310018 China Data Security Governance Zhejiang Engineering Research Center Hangzhou310018 China Zhejiang Lab Hangzhou311100 China Hangzhou Huawei Communication Technology Co. Ltd. Hangzhou310052 China

ISBN: (纸本)9783031545306

Federated learning is a distributed training method that integrates multi-party data information using privacy-preserving technologies through dispersed client data sets to jointly construct a global model under the coordination of a central server. However, in practical applications, there is a high degree of data distribution skewness among clients, which causes the optimization direction of the client models to diverge, resulting in model bias and reducing the accuracy of the global model. Existing methods require the calculation and transmission of much information to correct the optimization direction of the client models, or only roughly limit the deviation of the client models end-to-end, ignoring targeted processing of the internal structure of the model, resulting in unclear improvement effects. To address these problems, we propose a federated optimization algorithm FedECCR based on encoding contrast and classification correction. This algorithm divides the model into an encoder and a classifier. It utilizes prototype contrastive training of the model encoder and unbiased classification correction of the classifier. This approach notably improves the accuracy of the global model while maintaining low communication costs. We conducted experiments on multiple data sets to evaluate the validity of our method, and the quantified results showed that FedECCR can improve the global model classification accuracy by approximately 1% to 6% compared to FedAvg, FedProx, and MOON. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Classification (of information)

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Speed and Accuracy Tradeoff for LiDAR Data Based Road Boundary Detection

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IEEE/CAA Journal of Automatica Sinica 2021年第6期8卷 1210-1220页

作者： Guojun Wang Jian Wu Rui He Bin Tian State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130022China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the Qingdao Academy of Intelligent Industries ShandongChina

Road boundary detection is essential for autonomous vehicle localization and decision-making,especially under GPS signal loss and lane *** road boundary detection in structural environments,obstacle occlusions and large road curvature are two significant ***,an effective and fast solution for these problems has remained *** solve these problems,a speed and accuracy tradeoff method for LiDAR-based road boundary detection in structured environments is *** proposed method consists of three main stages:1)a multi-feature based method is applied to extract feature points;2)a road-segmentation-line-based method is proposed for classifying left and right feature points;3)an iterative Gaussian Process Regression(GPR)is employed for filtering out false points and extracting boundary *** demonstrate the effectiveness of the proposed method,KITTI datasets is used for comprehensive experiments,and the performance of our approach is tested under different road *** experiments show the roadsegmentation-line-based method can classify left,and right feature points on structured curved roads,and the proposed iterative Gaussian Process Regression can extract road boundary points on varied road shapes and traffic ***,the proposed road boundary detection method can achieve real-time performance with an average of 70.5 ms per frame.

关键词： 3D-LiDAR autonomous vehicle object detection point cloud road boundary

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Impacts of major volcanic eruptions over the past two millennia on both global and Chinese climates:A review

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Science China Earth Sciences 2024年第1期67卷 61-78页

作者： Weiyi SUN Deliang CHEN Guonian LÜ Liang NING Chaochao GAO Renhe ZHANG Bin WANG Jian LIU Key Laboratory for Virtual Geographic Environment Ministry of EducationState Key Laboratory Cultivation Base of Geographical Environment Evolution of Jiangsu ProvinceJiangsu Center for Collaborative Innovation in Geographical Information Resource Development and ApplicationSchool of Geography ScienceNanjing Normal UniversityNanjing 210023China Regional Climate Group Department of Earth SciencesUniversity of GothenburgGothenburg 40530Sweden College of Environmental and Resource Science Zhejiang UniversityHangzhou 310058China Department of Atmospheric and Oceanic Sciences&Institute of Atmospheric Sciences Fudan UniversityShanghai 200437China Department of Atmospheric Sciences and Atmosphere-Ocean Research Center University of Hawaii at ManoaHonoluluHI 96825USA Jiangsu Provincial Key Laboratory for Numerical Simulation of Large Scale Complex Systems School of Mathematical ScienceNanjing Normal UniversityNanjing 210023China Open Studio for the Simulation of Ocean-Climate-Isotope Qingdao National Laboratory for Marine Science and TechnologyQingdao 266237China

Major volcanic eruptions(MVEs)have attracted increasing attention from the scientific *** studies have explored the climatic impact of MVEs over the past two ***,proxy-based reconstructions and climate model simulations indicate divergent responses of global and China’s regional climates to ***,we used multiple data from observations,reconstructions,simulations,and assimilations to summarize the historical facts of MVEs,the characteristics and mechanisms of their climatic impact,and directions for future *** reviewed volcanic datasets and determined intensive MVE periods;these periods corresponded to the years 530–700,1200‒1460,and 1600‒1840 *** tropical MVEs,a substantial cooling effect is observed throughout the globe and China on the interannual-interdecadal time scales but an inconsistent cooling magnitude is detected between reconstructions and *** the first summer after tropical MVEs,a decrease in global and monsoonal precipitation is *** reconstructions and simulations,an increased precipitation is seen for the Yangtze River Basin,while large uncertainties in precipitation changes are present for other regions of *** drought can be induced by frequent eruptions and volcanism superimposed on low solar irradiation and internal *** affect climate directly through the radiative effect and indirectly by modulating internal variability,such as the El Niño‒Southern Oscillation(ENSO)and Atlantic Multidecadal Oscillation(AMO).However,changes in the phase,amplitude,and periodicity of ENSO and AMO after MVEs and the associated mechanisms remain controversial,which could account for model-reconstruction ***,other internal variability,uncertainties in reconstruction methods and aerosol‒climate models,and climate background may also induce model-reconstruction *** gaps and directions for future research are also discussed.

关键词： Major volcanic eruption Climate variability Mechanism Past two millennia Internal variability

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