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2023 IEEE International Conference on Memristive Computing and Applications, ICMCA 2023

作者： Zhao, Ximei Zhang, Hanyu Shao, Lijun Huang, Lili Li, Jiao School of Intelligent Manufacturing and Control Engineering Qilu Institute of Technology Jinan China Qilu Institute of Technology Jinan China College of Computer and Communication Engineering Qilu Institute of Technology Jinan China

ISBN: (纸本)9798350316230

In this article, we solve the fast finite-time stabilization as well as adaptive neural control design issues for a class uncertain stochastic nonlinear systems. By employing the mean value theorem, the pure-feedback form can be transformed into strict-feedback case. Firstly, a new fast finite-time control scheme is proposed in virtue of generalizing the fast finite-time adaptive control strategy for deterministic systems to the stochastic case. Next, a novel adaptive neural control strategy is developed to simultaneously deal with the stochastic nonlinear systems with completely unknown nonlinearities as well as the disturbances term. Then, stability analysis have been given based on a Jensen's inequality. © 2023 IEEE.

关键词： Feedback

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Method for Evaluating the Performance of Aircraft Collaborative Decision-Making Based on Dynamic Bayesian Network

Method for Evaluating the Performance of Aircraft Collaborat...

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2024 International Conference on Electronics and Devices, Computational Science, ICEDCS 2024

作者： Zhang, Wenbo Yu, Boxiao Tong, Jiahui Li, Jing Beijing Electro-Mechanical Engineering Institute National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China Beijing Institute of Technology School of Computer Science and Technology Beijing China

ISBN: (纸本)9798331527624

This research addresses the challenge of assessing equipment decision-making effectiveness in environments characterized by uncertainty and multiple influencing factors. We propose a novel approach involving the creation and optimization of a dynamic Bayesian network-based model tailored for equipment decision-making processes. The model facilitates a systematic evaluation of decision-making effectiveness by incorporating various factors, including equipment performance, environmental conditions, and enemy defensive capabilities. A comprehensive assessment system has been developed to simulate the penetration capabilities of different equipment through enemy defenses. Moreover, this study identifies potential errors in the effectiveness evaluation model by analyzing its performance in typical scenarios, pinpointing areas for enhancement. © 2024 IEEE.

关键词： Decision-making Dynamic Bayesian networks Equipment Simulation Uncertainty Management

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Wind disturbance compensated path-following control for fixed-wing UAVs in arbitrarily strong winds

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Chinese Journal of Aeronautics 2024年第2期37卷 431-445页

作者： Hao LU Lan GAO Yunda YAN Mingzhe HOU Chenliang WANG Hangzhou Innovation Institute Beihang UniversityHangzhou 310051China School of Information Science and Technology Hangzhou Normal UniversityHangzhou 311121China Department of Computer Science University College LondonLondon WC1E 6BTUnited Kingdom Center for Control Theory and Guidance Technology Harbin Institute of TechnologyHarbin 150001China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China

Wind is the primary challenge for low-speed fixed-wing unmanned aerial vehicles to follow a predefined flight *** cope with various wind conditions,this paper proposes a wind disturbance compensated path following control strategy where the wind disturbance estimate is incorporated with the nominal guiding vector field to provide the desired airspeed direction for the *** the control input vector for the outer-loop kinematic subsystem needs to satisfy a magnitude constraint,a scaling mechanism is introduced to tune the proportions of the compensation and nominal ***,an optimization problem is formulated to pursue a maximum wind compensation in strong winds,which can be solved analytically to yield two scaling factors.A cascaded inner-loop tracking controller is also designed to fulfill the outer-loop wind disturbance compensated guiding vector ***-fidelity simulation results under sensor noises and realistic winds demonstrate that the proposed path following algorithm is less sensitive to sensor noises,achieves promising accuracy in normal winds,and mitigates the deviation from a desired path in wild winds.

关键词： Path following Guiding vector field Wind disturbance Disturbance rejection Fixed wings

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Multi-Instance Multi-Label Classification from Crowdsourced Labels 39

Multi-Instance Multi-Label Classification from Crowdsourced ...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Wang, Ziquan Xia, Mingxuan Ren, Xiangyu Zhou, Jiaqing Lyu, Gengyu Hu, Tianlei Wang, Haobo School of Software Technology Zhejiang University China Institute of Blockchain and Data Security China College of Computer and Control Engineering Northeast Forestry University China ByteDance Hangzhou China College of Computer Science Beijing University of Technology China

ISBN: (纸本)157735897X

Multi-instance multi-label classification (MIML) is a fundamental task in machine learning, where each data sample comprises a bag containing several instances and multiple binary labels. Despite its wide applications, the data collection process involves matching multiple instances and labels, typically resulting in high annotation costs. In this paper, we study a novel yet practical crowdsourced multi-instance multi-label classification (CMIML) setup, where labels are collected from multiple crowd sources. To address this problem, we first propose a novel data generation process for CMIML, i.e., cross-label transition, where cross-label annotation error is more likely to appear rather than previous single-label transition assumption, due to the inherent similarity of localized instances from different classes. Then, we formally define the cross-label transition by cross-label transition matrices which are dependent across classes. Subsequently, we establish the first unbiased risk estimator for CMIML and further improve it through aggregation techniques, along with a rigorous generalization error bound. We also provide a practical implementation of cross-label transition matrix estimation. Comprehensive experiments on six benchmark datasets under various scenarios demonstrate that our algorithm outperforms the baselines by a large margin, validating its effectiveness in handling the CMIML problem. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Nameplates

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Robust control and data reconstruction for nonlinear epidemiological models using feedback linearization and state estimation

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Mathematical Biosciences and Engineering 2025年第1期22卷 109-137页

作者： Csutak, Balázs Szederkényi, Gábor Faculty of Information Technology and Bionics Pázmány Péter Catholic University Práter u. 50/A BudapestH-1083 Hungary Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Kende u. 13-17 BudapestH-1111 Hungary

It has been clearly demonstrated over the past years that control theory can provide an efficient framework for the solution of several complex tasks in epidemiology. In this paper, we present a computational approach for the state estimation based reference tracking control and historical data reconstruction using nonlinear compartmental epidemic models. The control model is given in nonlinear input-affine form, where the manipulable input is the disease transmission rate influenced by possible measures and restrictions, while the observed or computed output is the number of infected people. The control design is built around a simple SEIR model and relies on a feedback linearization technique. We examine and compare different control setups distinguished by the availability of state information, complementing the directly measurable data with an extended Kalman filter used for state estimation. To illustrate the capabilities and robustness of the proposed method, we carry out multiple case studies for output tracking and data reconstruction on Swedish and Hungarian data, all in the presence of serious model and parameter mismatch. Computation results show that a well-designed feedback, even in the presence of significant observation uncertainties, can sufficiently reduce the effect of modeling errors. © 2025 the Authors,

关键词： Feedback linearization

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SS-DBSCAN: Epsilon Estimation with Stratified Sampling for Density-Based Spatial Clustering of Applications with Noise

SS-DBSCAN: Epsilon Estimation with Stratified Sampling for D...

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2023 International Conference on Automation, control and Electronics Engineering, CACEE 2023

作者： Monko, Gloriana Joseph Kimura, Masaomi Shibaura Institute of Technology Graduate School Department of Functional Control Systems Tokyo Japan Shibaura Institute of Technology Department of Computer Science and Engineering Tokyo Japan

ISBN: (纸本)9798350309201

Clustering algorithms are crucial in uncovering hidden patterns and structures within datasets. Among the density-based clustering algorithms, DBSCAN (Density-Based Spatial Clustering of Applications with Noise) has gained considerable attention for its effectiveness in various applications. However, determining appropriate parameter values for this algorithm remains a challenging task. This paper presents a novel methodology for eps parameter estimation for an improved DBSCAN, namely SS-DBSCAN. The experimental results across nine datasets demonstrate the efficacy of our proposed method in accurately determining clusters with eps value from SS-DBSCAN algorithm. The clusters identified using estimated eps values by SS-DBSCAN align well with the inherent structure of the datasets, yielding better cluster results than the manually set parameters and other methods used for automatic estimations of the eps for DBSCAN. Our approach adapted well to the peculiarities of each dataset, whether dealing with different scales, dimensions, or densities;it proved the versatility and robustness across various datasets, thereby emphasizing its generalizability and potential for broader applications. © 2023 IEEE.

关键词： Parameter estimation

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computer System for Forming Compositions and Modeling the Properties of Secondary Polymer Materials 5

Computer System for Forming Compositions and Modeling the Pr...

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5th International Conference on control Systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2023

作者： Chistyakova, Tamara Balabekovna Novozhilova, Inna Vasilievna Razygraev, Aleksandr Sergeevich Goncharova, Tatyana Sergeevna Saint-Petersburg State Institute of Technology Department of Computer-Aided Design and Control Systems Saint Petersburg Russia

ISBN: (纸本)9798350309126

The computer system for forming compositions and modeling the secondary polymer materials properties is described in the article. The polymer compositions are formed using a customizable dataware, which includes a polymer wastes database and a knowledge base for recycling polymers into useful polymer products The knowledge base is developed using a product-frame model for representing knowledge about polymers and their compatibility. Modeling and research of the secondary polymers properties (strength, elasticity and density) is carried out based on the mathematical models. The result of the modeling system is a technological map for the composite polymer mixture synthesis and the production of a useful polymer product. The map includes data on the recipe, physicochemical and technological properties of polymers as secondary raw materials, polymer composition, hardware and technological design of the process, values of technological controlled variables of individual stages of processing. The use of a modeling system in production makes it possible to reduce the time required to solve the problem of selecting compositions, as well as reconfiguring production for a new task, improve the consumer characteristics of polymer products and reduce defects. © 2023 IEEE.

关键词： Materials properties

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TreeSwap: Data Augmentation for Machine Translation via Dependency Subtree Swapping

TreeSwap: Data Augmentation for Machine Translation via Depe...

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2023 International Conference Recent Advances in Natural Language Processing: Large Language Models for Natural Language Processing, RANLP 2023

作者： Nagy, Attila Lakatos, Dorina Barta, Botond Ács, Judit Department of Automation and Applied Informatics Budapest University of Technology and Economics Hungary Institute for Computer Science and Control Hungary

ISBN: (纸本)9789544520922

Data augmentation methods for neural machine translation are particularly useful when limited amount of training data is available, which is often the case when dealing with low-resource languages. We introduce a novel augmentation method, which generates new sentences by swapping objects and subjects across bisentences. This is performed simultaneously based on the dependency parse trees of the source and target sentences. We name this method TreeSwap. Our results show that TreeSwap achieves consistent improvements over baseline models in 4 language pairs in both directions on resource-constrained datasets. We also explore domain-specific corpora, but find that our method does not make significant improvements on law, medical and IT data. We report the scores of similar augmentation methods and find that TreeSwap performs comparably. We also analyze the generated sentences qualitatively and find that the augmentation produces a correct translation in most cases. Our code is available on Github1. © 2023 Incoma Ltd. All rights reserved.

关键词： Computational linguistics

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Medical Knowledge Graph:Data Sources,Construction,Reasoning,and Applications

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Big Data Mining and Analytics 2023年第2期6卷 201-217页

作者： Xuehong Wu Junwen Duan Yi Pan Min Li Computer Science and Engineering Central South UniversityChangsha 410083China School of Computer Science Hunan First Normal UniversityChangsha 410006China School of Computer Science and Engineering Central South UniversityChangsha 410083China Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518000China

Medical knowledge graphs(MKGs)are the basis for intelligent health care,and they have been in use in a variety of intelligent medical ***,understanding the research and application development of MKGs will be crucial for future relevant research in the biomedical *** this end,we offer an in-depth review of MKG in this *** research begins with the examination of four types of medical information sources,knowledge graph creation methodologies,and six major themes for MKG ***,three popular models of reasoning from the viewpoint of knowledge reasoning are discussed.A reasoning implementation path(RIP)is proposed as a means of expressing the reasoning procedures for *** addition,we explore intelligent medical applications based on RIP and MKG and classify them into nine major ***,we summarize the current state of MKG research based on more than 130 publications and future challenges and opportunities.

关键词： medical knowledge graph knowledge graph construction knowledge reasoning intelligent medical applications intelligent healthcare

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Disturbances Observer-Based Fixed-Time Sliding Mode control for Three-Level NPC Converters in Microgrid 22

Disturbances Observer-Based Fixed-Time Sliding Mode Control ...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Liu, Guangxin Shen, Xiaoning Zhang, Jianhua Gao, Yabin Liu, Jianxing School of Astronautics Harbin Institute of Technology Harbin China School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (纸本)9798331527471

This paper introduces a fixed-time sliding mode control (FTSMC) scheme that utilizes a fixed-time disturbance observer (FTDOB) for three-level neutral-point-clamped (3L-NPC) converters. Therein, a FTSMC with adaptive exponential coefficient is developed to regulate the dc-link voltage. Compared with existing methods, the proposed approach features a settling time upper bound that is independent of the initial error, which ensures the dynamic performance of the 3L-NPC converters. Furthermore, a FTDOB is employed to estimate external disturbances and act as feedforward compensation of the 3L-NPC converters to enhance its disturbances rejection ability. Finally, a series of simulation results illustrate the advantages of the proposed scheme by compared with several representative methods used in 3L-NPC converters. © 2024 IEEE.

关键词： Sliding mode control

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