检索结果-内蒙古大学图书馆

7th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2023

作者： Gong, Jiabao Fu, Weiming Kang, Yu Qin, Jiahu Xiao, Feng Department of Automation University of Science and Technology of China Hefei230027 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing102206 China

ISBN: (纸本)9789819733279

This paper proposes a multi-agent deep reinforcement learning (MADRL) based algorithm for charging control of multiple electric vehicles (EVs) in an electric vehicle charging station (EVCS) with dynamic operations. By taking the uncertainties of EV users’ behaviors and charging prices into consideration, a Markov game with multiple objectives is first established, where the individual objective of reducing EV charging costs and the collective objective of mitigating charging load fluctuations are both studied. Then, a multi-agent actor-double-critic (MAADC) algorithm with a unified advantage actor-critic framework is proposed, where two advantage functions are designed as the local and global critics, and the integrated actor is employed to balance the learning towards the individual and collective objectives. The simulation results obtained in a delicately built EVCS environment show the effectiveness of MAADC. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Correction to: Automated explainable and interpretable framework for anomaly detection and human activity recognition in smart homes (Neural Computing and Applications, (2025), 10.1007/s00521-025-10991-3)

引用

Neural Computing and Applications 2025年 1-2页

作者： Kim, Tae Hoon Ojo, Stephen Krichen, Moez Alamro, Meznah A. Mihoub, Alaeddine Sampedro, Gabriel Avelino School of Information and Electronic Engineering Zhejiang University of Science and Technology No. 318 Zhejiang Hangzhou China Department of Electrical and Computer Engineering College of Engineering Anderson University AndersonSC29621 United States Al-Baha University Al-Baha65528 Saudi Arabia ReDCAD Laboratory University of Sfax Sfax3038 Tunisia Department of Information Technology College of Computer and Information Science Princess Nourah Bint Abdul Rahman University Riyadh11564 Saudi Arabia Department of Management Information Systems College of Business and Economics Qassim University P.O. Box: 6640 Buraidah51452 Saudi Arabia Department of Computer Science University of the Philippines Diliman Quezon City1101 Philippines

In this article, the author’s name Stephen Ojo was incorrectly written as Stepehn Ojo and the affiliation details for author Stephen Ojo was incorrectly given as ‘Department of electrical and computer engineering, College of engineering Anderson, Anderson University, Anderson, SC 29621, USA’ but should have been ‘Department of electrical and computer engineering, College of engineering, Anderson University, Anderson, SC 29621, USA’. In addition, the affiliation details for author Gabriel Avelino Sampedro were incorrectly given as ‘College of computer Studies, De La Salle University, 2401 Taft Ave., Malate, 1004 Manila, Philippines and Faculty of Information and Communication Studies, University of the Philippines Open University, 4031 Los Baños, Philippines’ but should have been ‘Department of computer science, University of the Philippines Diliman, 1101 Quezon City, Philippines’. The original article has been corrected. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Mixture Gaussian Distribution-Based Collaborative Reinforcement Learning for 3D UAV Localization Optimization Against Jamming Attacks

Mixture Gaussian Distribution-Based Collaborative Reinforcem...

引用

2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Zhu, Yujiao Chen, Mingzhe Wang, Sihua Liu, Yuchen Li, Gaolei Yin, Changchuan Quek, Tony Q.S. Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Network Beijing100876 China Singapore University of Technology and Design 487372 Singapore University of Miami Department of Electrical and Computer Engineering Institute for Data Science and Computing Coral GablesFL33146 United States North Carolina State University Department of Computer Science RaleighNC27695 United States Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai200240 China

ISBN: (纸本)9798350351255

In this paper, the optimization of unmanned aerial vehicle (UAV) localization under jamming attacks is studied. In the considered network, a base station (BS) collaborates with an active UAV to localize a target UAV. During this positioning process, a jamming UAV transmits discontinuous signals to passive UAVs to interfere the distance information measurement. To localize the target UAV under jamming attacks, the BS jointly use two localization methods: 1) generative adversarial network (GAN)-based positioning method and 2) time difference of arrival (TDOA)-based positioning method. Since GAN-based positioning method cannot defense in a strong jamming signal while TDOA-based positioning method may consume more energy and sacrifice localization accuracy, the BS must select an appropriate positioning method (GAN-based or TDOA-based methods) and four distance measurement information of passive UAVs to estimate the position of the target UAV. This problem is formulated as an optimization problem whose goal is to minimize the positioning error between the estimated and the ground truth positions of the target UAV while considering jamming attacks and the trajectory of passive UAVs. To solve this problem, we propose a mixture Gaussian distribution model-based collaborative reinforcement learning (RL) method which enables the active UAV to determine its transmit power and trajectory, and enables the BS to select the most appropriate subsets of distance measurement information and the optimal positioning method according to the movement of passive UAVs and the unknown jamming attack pattern of the jamming UAV. Simulation results show the proposed method can reduce the positioning error of the target UAV by up to 36.5% compared to the method that does not consider the GAN-based positioning method. © 2024 IEEE.

关键词： Gaussian distribution

来源：评论

学校读者我要写书评

暂无评论

Exponential Weighted Moving Average-Based Variational Mode Decomposition Method for Fault Diagnosis of Vehicle Batteries 13

Exponential Weighted Moving Average-Based Variational Mode D...

引用

13th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2024

作者： Wu, Penghao Tao, Hongfeng Tian, Engang Yin, Tangwen Chen, Hongtian Chen, Yiyang School of Mechanical and Electrical Engineering Soochow University Suzhou215137 China Jiangnan University Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Wuxi214122 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China Shanghai Jiao Tong University Department of Automation Shanghai200240 China

ISBN: (纸本)9798350361674

In recent years, the rapid advancement of electric vehicles has heightened concerns regarding the safety of high-energy batteries. Consequently, there has been a significant focus on the development of fault diagnosis technologies for batteries. Intelligent fault diagnosis (IFD), particularly data-driven approaches, represents a crucial methodology in addressing this concern. This paper proposes a data-driven approach, for IFD in high-energy batteries utilized in electric vehicles. The proposed Exponentially Weighted Average Variational Mode Decomposition (EWVMD) method overcomes these limitations by employing the exponential weighted moving average (EWMA) technique to smooth collected time-series voltage data. This process reduces noise, accentuates abnormal change trends, and yields secondary data with enhanced features. Subsequently, variational mode decomposition (VMD) is applied to the secondary data. The resulting decomposed sub-mode curves (intrinsic mode functions - IMFs) and the change trends of the residual curve, in conjunction with a fault threshold tailored to actual working conditions, are utilized to ascertain the occurrence of faults. Design verification experiments, the C42MSA electric vehicle power supply battery undergoes charging and discharging tests with injected faults at fixed intervals. The collected fault signals are then subjected to fault diagnosis using EWVMD. Results demonstrate the algorithm's superior detection effectiveness and increased sensitivity to fault signals compared to traditional methods. © 2024 IEEE.

关键词： Variational mode decomposition

来源：评论

学校读者我要写书评

暂无评论

UAV-RIS-Aided Energy-Efficient and QoS-Aware Emergency Communications Based on DRL 100

UAV-RIS-Aided Energy-Efficient and QoS-Aware Emergency Commu...

引用

100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Hu, Jiawei Ju, Ying Wang, Haoyu Liu, Lei Pei, Qingqi Shee, Y.G. Zhu, Xiaojie Wu, Celimuge University of California Department of Electrical Engineering and Computer Science IrvineCA92697 United States Xidian University Guangzhou Institute of Technology Guangzhou510555 China Xi'an University of Posts Telecommunications Shaanxi Key Laboratory of Information Communication Network and Security Xi'an710121 China Universiti Tunku Abdul Rahman Department of Electrical and Electronic Engineering Kajang43000 Malaysia King Abdullah University of Science and Technology Department of Computer Electrical and Mathematical Sciences and Engineering Thuwal239556900 Saudi Arabia The University of Electro-Communications Graduate School of Informatics and Engineering Tokyo182-8585 Japan

ISBN: (纸本)9798331517786

Ensuring reliable communication can be incredibly challenging in emergencies due to the breakdown of conventional infrastructure. However, a promising solution is on the horizon: the integration of reconfigurable intelligent surfaces (RIS) onto unmanned aerial vehicles (UAV), known as UAV-RIS. This innovative approach holds the potential to offer agile and adaptable communication services during crises, overcoming the limitations of traditional systems. This paper establishes an innovative UAV-RIS system with an active RIS to enhance the uplink communication between ground devices (GDs) and the air base station (ABS). We present an advanced communication strategy utilizing deep reinforcement learning (DRL) for UAV-RIS-supported uplink communication in dynamic emergencies. This scheme is designed to optimize the energy efficiency of the UAV-RIS communication system while adhering to quality of service (QoS) constraints for all GDs. It achieves this by jointly optimizing the trajectory of the UAV-RIS and the phase of the active RIS, ensuring efficient and reliable communication in challenging environments. To optimize the performance of the system, we propose a hierarchical Proximal Policy Optimization (H-PPO) algorithm and the upper and lower layers of H-PPO optimize the trajectory and phase control, respectively. Simulation results demonstrate that our scheme can effectively learn the communication strategy to enhance the performance of dynamic emergency communication networks. © 2024 IEEE.

关键词： active reconfigurable intelligent surface deep reinforcement learning quality of service UAV trajectory

来源：评论

学校读者我要写书评

暂无评论

Sequential Transfer with Multi-Objective Genetic Algorithm for Feature Selection of Small, High-Dimensional Datasets

Sequential Transfer with Multi-Objective Genetic Algorithm f...

引用

Congress on Evolutionary Computation

作者： Parth C. Upadhyay G. N. DeSouza John A. Lory Department of Electrical Engineering and Computer Science (EECS) Vision-Guided and Intelligent Robotics (ViGIR) Laboratory Division of Plant Sciences University of Missouri Columbia MO

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

Performing feature selection on a small number of instances with high-dimensional datasets poses a needed challenge in preventing over-fitting. To address this issue, this paper proposes a sequential transfer-learning approach combined with a multi-objective genetic algorithm (STMO-GA) for feature selection. Firstly, for the multi-objective component of our method, we employ a Non-dominated Sorting Genetic Algorithm (NSGA-II) to generate a Pareto front. Then, features are ranked based on their number of appearances in the same Pareto front. Next, during the sequential knowledge transfer process, the ranked features are iteratively selected until a predetermined $n$ number of features remains. This feature subspace is further refined by a k-fold cross-validation operation, starting from the rank-one feature, to determine the cut-off of the $n$ features that will remain. Comparative evaluations against both GA-based as well as traditional feature selection methods demonstrate that the proposed method achieves superior classification accuracy, while retaining the smallest number or a comparable number of features.

关键词： Accuracy Evolutionary computation Feature extraction Genetics Linear programming Robustness Optimization

来源：评论

学校读者我要写书评

暂无评论

Research on Causal Model Construction and Fault Diagnosis of Control Systems 7th

Research on Causal Model Construction and Fault Diagnosis of...

引用

7th International Conference on Computing, Control and Industrial engineering, CCIE 2023

作者： Zhu, Qun Chen, Zhi Liu, Jie Xu, Zhuoran Wen, Juan Yang, Jinghua Jian, Yifan School of Computer Science University of South China Hengyang421200 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu610064 China School of Electrical Engineering University of South China Hengyang421200 China

ISBN: (纸本)9789819927296

Fault diagnosis of complex control systems is a difficult and hot topic of research at this stage. In order to explore the internal operation characteristics of complex control systems and fault propagation methods to achieve efficient and accurate fault diagnosis, this paper studies control system fault diagnosis methods based on cause-effect relationships, analyzes the role relationship between system components from the perspective of control equation structure, proposes the method of constructing cause-effect diagram models with control equations, and uses the algorithm of way to implement, and then combine the information flow to quantify the causal effect quantifiably, when the system steady state is disrupted, the information flow produces a jump, so as to extend the fault diagnosis reasoning method. The fault diagnosis is verified by simulation of the pressure control system of the nuclear power plant regulator, and the experimental results verify the effectiveness of the proposed method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Failure analysis

来源：评论

学校读者我要写书评

暂无评论

An application of the shortest path algorithm for the identification of weak MHD mode

引用

Plasma science and Technology 2023年第8期25卷 19-27页

作者：黄卓毛飞越丁永华田微黄名响李达沈呈硕王能超梁云峰 the J-TEXT Team College of Computer Science South-Central Minzu UniversityWuhan 430074People's Republic of China International Joint Research Laboratory of Magnetic Confinement Fusion and Plasma Physics State Key Laboratory of Advanced Electromagnetic Engineering and TechnologySchool of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhan 430074People's Republic of China Forschungszentrum Jülich GmbH Institut für Energie-und Klimaforschung-PlasmaphysikPartner of the Trilateral Euregio Cluster(TEC)Jülich 52425Germany 不详

The identification of magnetohydrodynamic(MHD)modes is a crucial issue in the control of magnetically confined *** paper proposes a novel method for identifying the evolution of MHD modes from a signal with a low signal-to-noise *** proposed method generates a weighted directed graph from the time-frequency spectrum and calculates the evolution of the mode frequency by solving the shortest *** method addresses the limitations posed by the lack of data channels and the disturbance of noise in the estimation of mode frequency and yields much better results compared to traditional *** is demonstrated that,using this method,the evolution of an unlocked tearing mode was more accurately calculated on the J-TEXT *** method remains feasible even with a low signal-to-noise ratio of 0.5,as shown by its ***,with appropriate parameters,this method can be applied to not only signals with MHD modes,but also to general signals with continuous modes.

关键词： plasma physics magnetohydrodynamic pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Augmented Feature Representation with Parallel Convolution for Cross-domain Facial Expression Recognition 16th

Augmented Feature Representation with Parallel Convolution ...

引用

16th Chinese Conference on Biometric Recognition, CCBR 2022

作者： Yang, Fan Xie, Weicheng Zhong, Tao Hu, Jingyu Shen, Linlin Computer Vision Institute School of Computer Science and Software Engineering Shenzhen University Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen China

ISBN: (纸本)9783031202322

Facial expression recognition (FER) has made significant progress in the past decade, but the inconsistency of distribution between different datasets greatly limits the generalization performance of a learned model on unseen datasets. Recent works resort to aligning feature distributions between domains to improve the cross-domain recognition performance. However, current algorithms use one output each layer for the feature representation, which can not well represent the complex correlation among multi-scale features. To this end, this work proposes a parallel convolution to augment the representation ability of each layer, and introduces an orthogonal regularization to make each convolution represent independent semantic. With the assistance of a self-attention mechanism, the proposed algorithm can generate multiple combinations of multi-scale features to allow the network to better capture the correlation among the outputs of different layers. The proposed algorithm achieves state-of-the-art (SOTA) performances in terms of the average generalization performance on the task of cross-database (CD)-FER. Meanwhile, when AFED or RAF-DB is used for the training, and other four databases, i.e. JAFFE, SFEW, FER2013 and EXPW are used for testing, the proposed algorithm outperforms the baselines by the margins of 5.93% and 2.24% in terms of the average accuracy. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Design of new resonant magnetic perturbation coils on the J-TEXT tokamak

引用

Plasma science and Technology 2023年第11期25卷 142-149页

作者：黄卓周松樊金荣李达饶波王能超丁永华毛飞越黄名响田微陈忠勇陈志鹏梁云峰 the J-TEXT Team College of Computer Science South-Central Minzu UniversityWuhan 430074People’s Republic of China International Joint Research Laboratory of Magnetic Confinement Fusion and Plasma Physics State Key Laboratory of Advanced Electromagnetic Engineering and TechnologySchool of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhan 430074People’s Republic of China Forschungszentrum Jülich GmbH Institut für Energie-und Klimaforschung-PlasmaphysikPartner of the Trilateral Euregio Cluster(TEC)Jülich D-52425Germany 不详

The resonant magnetic perturbation(RMP)system is a powerful auxiliary system on *** the J-TEXT tokamak,a set of new in-vessel coils is designed to enhance the amplitude of the *** new coils are designed to be two-turn saddle *** two-turn saddle coils have been optimized in terms of their structure,support,and protection components to overcome the limitations of the narrow in-vessel space,resulting in a compact coil module that can be accommodated in the *** verify the feasibility of this design,an electromagnetic simulation is performed to investigate the electrical parameters and the generated field of the coils.A multi-field coupled simulation is performed to investigate the capacity of heat *** a result of these efforts,the new RMP coils have been successfully installed on the J-TEXT *** has significantly enhanced the RMP amplitude and been widely applied in experiments.

关键词： fusion engineering tokamak resonant magnetic perturbation coil multi-field coupled simulation(Some fioures may appeari in colour only in the online iournal)

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：