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第35届中国控制会议

作者： LIU Xiwei LI Ping Department of Computer Science and Technology Tongji University Key Laboratory of Embedded System and Service Computing Ministry of Education

ISBN: (纸本)9789881563910

In this paper, we consider a general and practical complex network model, in which there exist couplings with and without time delays, and the coupled functions among nodes are also nonlinear. For this network model, we investigate its finite-time synchronization by designing some general static and adaptive controllers respectively. Using the finite-time stability theory, some useful finite-time synchronization criteria are derived. Finally, numerical simulations are given to demonstrate the correctness of our theoretical results.

关键词： Synchronization Finite-time Nonlinear Coupling Time Delay

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Macro liveness graph and liveness of ω-independent unbounded nets

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Science China(Information Sciences) 2015年第3期58卷 132-141页

作者： WANG ShouGuang GAN MengDi ZHOU MengChu School of Information and Electronic Engineering Zhejiang Gongshang University Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji University Department of Electrical and Computer Engineering New Jersey Institute of Technology

Liveness is a basic property of a system and the liveness issue of unbounded Petri nets remains one of the most difficult problems in this *** work proposes a novel method to decide the liveness of a class of unbounded generalized Petri nets calledω-independent unbounded nets,breaking the existing limits to one-place-unbounded *** algorithm to construct a macro liveness graph(MLG)is developed and a critical condition based on MLG deciding the liveness ofω-independent unbounded nets is *** are provided to demonstrate its effectiveness.

关键词： discrete event system(DES) Petri nets complex systems liveness property analysis

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Cluster synchronization of nonlinearly coupled networks via periodically intermittent pinning control

Cluster synchronization of nonlinearly coupled networks via ...

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第三十二届中国控制会议

作者： LIU Xiwei CHENG Jiujun Department of Computer Science and Technology Tongji Universityand the Key Laboratory of Embedded System and Service ComputingMinistry of Education

ISBN: (纸本)9781479900305

In this paper,the cluster synchronization problem for nonlinearly coupled networks under periodically intermittent pinning control is *** first,a sufficient condition to guarantee cluster synchronization is ***,an adaptive intermittent control algorithm is designed to the control strength and its validity is rigorously ***,some numerical examples are presented to demonstrate the correctness of obtained theoretical results.

关键词： Cluster synchronization Adaptive Nonlinearly coupled Periodically Intermittent pinning.

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Synchronization of nonlinearly coupled complex networks under periodically intermittent pinning control

Synchronization of nonlinearly coupled complex networks unde...

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第25届中国控制与决策会议

作者： Xiwei Liu Cheng Cheng Department of Computer Science and Technology Tongji University and the Key Laboratory of Embedded System and Service Computing Ministry of Education

ISBN: (纸本)9781467355339

In this paper, we investigate the synchronization problem for nonlinearly coupled networks under periodically intermittent pinning control, where the coupling matrix denoting network topology is assumed to be symmetric. A sufficient condition to guarantee global synchronization is presented. Moreover, a centralized adaptive intermittent control is designed and its validity is rigorously proved. Finally, some numerical examples are presented to demonstrate the correctness of obtained theoretical results.

关键词： Synchronization, Consensus, Complex networks, Nonlinearly coupled, Periodically, Intermittent pinning, Adaptive control.

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A transactional-behavior-based hierarchical gated network for credit card fraud detection

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IEEE/CAA Journal of Automatica Sinica 2025年

作者： Xie, Yu Zhou, MengChu Liu, Guanjun Wei, Lifei Zhu, Honghao De Meo, Pasquale College of Information Engineering Shanghai Maritime University Shanghai201306 China School of Information and Electronic Engineering Zhejiang Gongshang University Hangzhou310018 China Helen and John C. Hartmann Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States Key Laboratory of Embedded System and Service Computing Ministry of Education Department of Computer Science Tongji University Shanghai201804 China College of Computer Science and Information Engineering Bengbu University Bengbu233030 China Department of Ancient and Modern Civilizations University of Messina Messina98166 Italy

The task of detecting fraud in credit card transactions is crucial to ensure the security and stability of a financial system, as well as to enforce customer confidence in digital payment systems. Historically, credit card companies have used rule-based approaches to detect fraudulent transactions, but these have proven inadequate due to the complexity of fraud strategies and have been replaced by much more powerful solutions based on machine learning or deep learning algorithms. Despite significant progress, the current approaches to fraud detection suffer from a number of limitations: for example, it is unclear whether some transaction features are more effective than others in discriminating fraudulent transactions, and they often neglect possible correlations among transactions, even though they could reveal illicit behaviour. In this paper, we propose a novel credit card fraud detection (CCFD) method based on a transaction behaviour-based hierarchical gated network. First, we introduce a feature-oriented extraction module capable of identifying key features from original transactions, and such analysis is effective in revealing the behavioural characteristics of fraudsters. Second, we design a transaction-oriented extraction module capable of capturing the correlation between users' historical and current transactional behaviour. Such information is crucial for revealing users' sequential behaviour patterns. Our approach, called transactional-behaviour-based hierarchical gated network model (TbHGN), extracts two types of new transactional features, which are then combined in a feature interaction module to learn the final transactional representations used for CCFD. We have conducted extensive experiments on a real-world credit card transaction dataset with an increase in average F1 between 1.42% and 6.53% and an improvement in average AUC between 0.63% and 2.78% over the state of the art. © 2025 Institute of Electrical and Electronics Engineers Inc.. All right

关键词： Deep learning

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Feedback-based Coarse Time-Granularity POI Recommendation and Itinerary Planning

Feedback-based Coarse Time-Granularity POI Recommendation an...

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2021 China Automation Congress, CAC 2021

作者： Zong, Jie Ding, Zhijun The Key Laboratory of Embedded System and Service Computing Ministry of Education TONGJI University Shanghai China

ISBN: (纸本)9781665426473

For tourists, planning their own travel itinerary to a strange city is really challenging. Although there are many researches on Point of Interests (POIs) recommendation and itinerary planning, two problems occur in currently proposed recommendation algorithms. First, the time granularity of the algorithms is too fine. POI recommendation should be considered within a more coarse-grained time factor. For example, a visitor wouldn't like to visit a water park in winter, although he appears to love such places. However, seldom researches have taken this into consideration. Second, most of the algorithms build their models based on the tourists' trajectory, which means, they did not consider users' feedback. In fact, quite a number of tourists do not like their travel experience and give negative feedbacks after their visits. In this situation, we shouldn't recommend similar POIs to this user because he may not like such kind of scenic spots at all. To address these two problems, this paper proposes an algorithm called Feedback-based Coarse Time-Granularity POI Recommendation, which can extract information from comments and distinguish tourists' attitudes towards the POIs they have visited. At the same time, the coarse-grained time factor is considered while making recommendations. In addition, an itinerary planning algorithm is proposed. Experiments show that our algorithm can reach SOTA. © 2021 IEEE

关键词： Parks

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Adaptive Random Forest with Dynamic Detectors for Evolving Data Stream Classification 23

Adaptive Random Forest with Dynamic Detectors for Evolving D...

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9th International Conference on computing and Artificial Intelligence, ICCAI 2023

作者： Jin, Xuancheng Zhang, Yaying Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

ISBN: (纸本)9781450399029

Evolving data streams containing concept drift breaks the assumption that data are independent and identically distributed (IID) in traditional machine learning models. A series of ensemble-based models have been adapted to data stream learning tasks due to the abilities of dynamic partially update and cooperate with drift detection methods. Adaptive Random Forests (ARF), one of the state-of-the-art in the stream setting, encounters high resource requirements in both efficiency and memory like all ensemble methods. We are committed to reducing running cost without compromising ARF’s performance. In this paper, we propose the Adaptive Random Forest with Dynamic Detectors (ARFDD) which utilizes diversity measurement to combine homogeneous detectors and split heterogeneous ones accordingly, leads to lower computing costs and thus speed up in applications. Experiments on all 8 synthetic and 4 real datasets show a great CPU-time thrift while avoiding performance degradation. © 2023 Copyright held by the owner/author(s).

关键词： Learning systems

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Research on Behavior Element Decision of Cloud Edge Collaboration Capability Based on 5g Automatic Driving Scene 5

Research on Behavior Element Decision of Cloud Edge Collabor...

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5th IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2021

作者： Yan, Chungang Sheng, Shuo Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

ISBN: (纸本)9781665415989

In order to meet the cloud side requirements of various traffic business scenarios, the construction of traffic cloud side collaboration platform realizes the collaboration and unification of various business resources and data on both sides of the cloud side, and the cloud side integration realizes the real-time and efficient "vehicle road cloud side"collaboration of traffic. In order to quickly meet the needs of various scenarios and provide customized cloud edge capability services, by drawing on the experience and technology R D capabilities of Companies in the industry, it helps to shorten the overall development period of the platform, reduce costs and technical risks, and quickly form product capabilities. Based on the cloud edge collaboration capability, the super edge node collects structured and unstructured data in real time, uses the edge computing power to label, filter and design thresholds, so as to detect and filter the scene behavior elements in 5g + traffic scenarios, further clarify the actor's data, gather it to the cloud for research and judgment, and improve the global decision-making ability of the cloud, Improve the real-time flow of dynamic traffic element resources. © 2021 IEEE.

关键词： 5G mobile communication systems

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STMGT: A Long-Term Traffic Forecasting Method Based on Spatial-Temporal Multi-View Graph Transformer 24

STMGT: A Long-Term Traffic Forecasting Method Based on Spati...

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5th International Conference on Artificial Intelligence and Computer Engineering, ICAICE 2024

作者： Zheng, Fengkai The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

ISBN: (纸本)9798400718007

Accurate long-term traffic forecasting is crucial for urban traffic management and planning. Existing methods focus mainly on short-term predictions and struggle with long-term spatial-temporal dependencies due to computational complexities. We propose a Spatial-Temporal Multi-View Graph Transformer (STMGT) based on spatial-temporal sequence decomposition. STMGT enhances long-term forecasting by decomposing traffic sequences into temporal position embeddings, periodicity-trend features, and residual components. This approach captures long-term correlations while managing computational cost by dividing data into multiple time blocks. A multi-head graph attention mechanism is used to explore dynamic spatial correlations. Experimental results on real-world datasets show that STMGT significantly outperforms baseline models, proving it effective for long-term traffic prediction. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： graph attention mechanism

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Will the fibers of the future be considered fibers?

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National Science Review 2024年第10期11卷 15-17页

作者： Dewen Xu Ya Liu Hailiang Wang Wei Yan Changjun Jiang Meifang Zhu State Key Laboratory for Modification of Chemical Fibers and Polymer Materials College of Materials Science and Engineering Donghua University Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Department of Computer Science and Technology Tongji University

Fiber materials are key materials that have changed human history and promoted the progress of human civilization. In ancient times, humans used feathers and animal skins for clothing, and later they widely employed natural fibers such as cotton, hemp, silk and wool to make fabrics(Fig. 1a). Chinese ancestors had mastered the art of natural fiber weaving as early as the Neolithic *** thousand years ago, people were already familiar with and adept at techniques for spinning natural fibers [1].

关键词： future will considered fibers

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