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International Conference on Intelligent Transportation

作者： Siwen Yang Yunwen Xu Dewei Li Chen Zhang School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

Many studies have demonstrated the potential benefits of connected and autonomous vehicles (CAVs) platooning to energy consumption and traffic efficiency. However, how to implement platoon formation, which assigns and regulates vehicles scattered in different lanes to platoons, while reducing vehicle delay and time consumption remains an open issue. Besides, most existing studies require a predetermined platoon configuration, which decreases maneuverability. This paper proposes a multilane platoon formation strategy with undefined configurations. The vehicle sequence in newly formed platoons along with the longitudinal trajectories of all vehicles before changing lanes is optimized in a nonlinear programming model. The multi-objective function considers the average velocity of all CAVs and the time consumption of formation. A Fibonacci search algorithm with an embedded mixed integer linear programming (MILP) model is developed to obtain solutions efficiently. The numerical experiments indicate the superiority of the proposed method in optimizing the vehicles' trajectories and improving multi-lane platoon formation efficiency.

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AUTOSIM:Automated Urban Traffic Operation Simulation via Meta-Learning

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IEEE/CAA Journal of Automatica Sinica 2023年第9期10卷 1871-1881页

作者： Yuanqi Qin Wen Hua Junchen Jin Jun Ge Xingyuan Dai Lingxi Li Xiao Wang Fei-Yue Wang Zhejiang Lab Hangzhou 310030China ECARX Technology Co. Ltd.Shanghai 201811China IEEE Zhejiang Supcon Information Company Ltd. Hangzhou 310052China the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Indiana University-Purdue University Indianapolis(IUPUI) IndianapolisIndiana 46202 USA School of Artificial Intelligence Anhui UniversityHefei 230039China

Online traffic simulation that feeds from online information to simulate vehicle movement in real-time has recently seen substantial advancement in the development of intelligent transportation systems and urban traffic *** has been a challenging problem due to three aspects:1)The diversity of traffic patterns due to heterogeneous layouts of urban intersections;2)The nature of complex spatiotemporal correlations;3)The requirement of dynamically adjusting the parameters of traffic models in a real-time *** cater to these challenges,this paper proposes an online traffic simulation framework called automated urban traffic operation simulation via meta-learning(AUTOSIM).In particular,simulation models with various intersection layouts are automatically generated using an open-source simulation tool based on static traffic geometry *** a meta-learning technique,AUTOSIM enables an automated learning process for dynamic model settings of traffic scenarios featured with different spatiotemporal ***,AUTOSIM is capable of adapting traffic model parameters according to dynamic traffic information in real-time by using a *** computational experiments,we demonstrate the effectiveness of the meta-learningbased framework that is capable of providing reliable supports to real-time traffic simulation and dynamic traffic operations.

关键词： Conditional generative adversarial network signalized urban networks short-term link speed prediction

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Robust Adatpive Sliding Mode Tracking control for an AUV

Robust Adatpive Sliding Mode Tracking Control for an AUV

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2021 China Automation Congress, CAC 2021

作者： Zheng, Jiaqi Yu, Wenbin Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781665426473

In our work, the research on trajectory tracking with time-varying disturbances is investigated via robust adaptive sliding mode control (RASMC). We first design a nonsingular sliding mode surface for tracking error system and show that the sliding mode surface is continuous. Then, since the underwater environment is very complex and the AUV's mathematical model is strongly nonlinear and highly coupled with uncertainties, we propose the robust adaptive law to ensure the superior robust performance of AUV system. The obtained results suggest that the proposed controller can reduce chattering and tracking error by designing a nonsingular sliding mode surface. © 2021 IEEE

关键词： Environmental regulations

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Distributed Short-Term Load Forecasting for Interconnecting Power systems

Distributed Short-Term Load Forecasting for Interconnecting ...

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2021 China Automation Congress, CAC 2021

作者： Guan, Yaonan Li, Dewei Xi, Yugeng Department of Automation Shanghai Jiao Tong University China Key Laboratory of System Control and Information Processing Ministry of Education of China China

ISBN: (纸本)9781665426473

The social factors which exert an important influence on the load variations are difficult to adopt in centralized load forecasting models. A distributed short-term load forecasting method is proposed in this paper to compensate for the lack of social factors in load forecasting of the interconnecting power system network. In this method, we focus on the influence of social factors rather than the elements themselves. First, a classification method is proposed to arrange systems into several functional groups according to their load curve feature. Second, the interactions between systems are introduced into the model to represent social factors' influence on systems. Finally, experiments are conducted to verify the advantage of the proposed model. © 2021 IEEE

关键词： Data mining

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Corrigendum to "Hyperledger sawtooth based supplychain traceability system for counterfeit drugs" [Comput. Ind. Eng. 190 (2024) 110021] (Computers & Industrial Engineering (2024) 190, (S0360835224001426), (10.1016/***.2024.110021))

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Computers and Industrial Engineering 2025年 204卷

作者： Nawaz, Anum Wang, Liguan Irfan, Muhammad Westerlund, Tomi Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University Shanghai China Turku Intelligent and Embedded Robotic Systems Lab Faculty of Technology University of Turku Finland

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Systematic Cloud-Based Optimization: Twin-Fold Moth Flame Algorithm for VM Deployment and Load-Balancing

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Intelligent Automation & Soft Computing 2024年第3期39卷 477-510页

作者： Umer Nauman Yuhong Zhang Zhihui Li Tong Zhen Information Science and Engineering College Henan University of TechnologyZhengzhou450001China School of Artificial Intelligence and Big Data Henan University of TechnologyZhengzhou450001China Key Laboratory of Grain Information Processing and Control Ministry of EducationHenan University of TechnologyZhengzhou450001China

Cloud computing has gained significant recognition due to its ability to provide a broad range of online services and ***,existing commercial cloud computing models demonstrate an appropriate design by concentrating computational assets,such as preservation and server infrastructure,in a limited number of large-scale worldwide data *** the deployment of virtual machines(VMs)is crucial in this scenario to ensure system dependability,performance,and minimal latency.A significant barrier in the present scenario is the load distribution,particularly when striving for improved energy consumption in a hypothetical grid computing *** design employs load-balancing techniques to allocate different user workloads across several virtual *** address this challenge,we propose using the twin-fold moth flame technique,which serves as a very effective optimization *** intentionally designed the twin-fold moth flame method to consider various restrictions,including energy efficiency,lifespan analysis,and resource *** provides a thorough approach to evaluating total costs in the cloud computing *** assessing the efficacy of our suggested strategy,the study will analyze significant metrics such as energy efficiency,lifespan analysis,and resource *** investigation aims to enhance cloud computing techniques by developing a new optimization algorithm that considers multiple factors for effective virtual machine placement and load *** proposed work demonstrates notable improvements of 12.15%,10.68%,8.70%,13.29%,18.46%,and 33.39%for 40 count data of nodes using the artificial bee colony-bat algorithm,ant colony optimization,crow search algorithm,krill herd,whale optimization genetic algorithm,and improved Lévy-based whale optimization algorithm,respectively.

关键词： Optimizing cloud computing deployment of virtual machines load-balancing twin-fold moth flame algorithm grid computing computational resource distribution data virtualization

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Characteristic Mode Cancellation for Radiation Pattern Decoupling of Asymmetric Dipole Antennas

Characteristic Mode Cancellation for Radiation Pattern Decou...

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Cross Strait Quad-Regional Radio Science and Wireless Technology Conference (CSRWTC)

作者： Yu-Zhuo Deng Nan Yang Kai Lu Jingchang Nan Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems School of Electronics and Information Technology (School of Microelectronics) Sun Yat-sen University Guangzhou China Liaoning Key Laboratory of Radio Frequency and Big Data for Intelligent Applications Liaoning Technical University Huludao China

ISBN: (数字)9798331507794

ISBN: (纸本)9798331507800

1 × 2 asymmectric dipole antennas with radiation pattern decoupling (RPD) characteristic are presented in this paper. These two dipole antennas are connected by a cross shaped strip. Characteristic mode analysis (CMA) is used to analyze and design this kind of antenna. Observed with CMA, a pair of common and differential characteristic modes superposed together to obtain little current distribution under the coupled dipole antenna. Therefore, RPD characteristic can be realized with high isolation. To verify the concept, a prototype is designed, fabricated, and measured, with good agreement observed. A measured 22.5% 10-dB impedance bandwidth can be obtained, over which the measured isolation is higher than 23 dB. It should be mentioned that RPD effect can be found over entire impedance band, which is highly desired for practical applications.

关键词： Antenna measurements Wireless communication Impedance measurement Philosophical considerations Dipole antennas Prototypes Bandwidth Impedance Gain Antenna radiation patterns

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Exchange Strategies for Multi-Colony Ant Algorithms in Dynamic Environments 13

Exchange Strategies for Multi-Colony Ant Algorithms in Dynam...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Mavrovouniotis, Michalis Li, Changhe Yazdani, Danial Handjimitsis, Diofantos Eratosthenes Centre of Excellence Limassol Cyprus Cyprus University of Technology Department of Civil Engineering and Geomatics Limassol Cyprus School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China University of Technology Sydney Faculty of Engineering & Information Technology Sydney Australia

ISBN: (纸本)9798350308365

In dynamic optimization problems where optimal solutions change over time, traditional ant colony optimization (ACO) algorithms face limitations. This study explores the adaptation of multi-colony ACO algorithms, known for their enhanced search capabilities in stationary problems, to tackle optimization problems in dynamic environments. Various strategies for exchanging information between colonies, which is a critical factor influencing algorithm performance, are investigated. Using the dynamic traveling salesman problem as a foundation, we generate test cases to reflect real-world complexities. Our results on a set of problem instances reveal that the choice of communication strategy between colonies significantly impacts the adaptability and efficiency of multi-colony ACO algorithms in tracking moving optimum. © 2024 IEEE.

关键词： Ant colony optimization

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3D Vision Based Lamination Gap Detection of Carbon Fiber Composite

3D Vision Based Lamination Gap Detection of Carbon Fiber Com...

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2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Xu, Yuanye Yuan, Libiao Liang, Wei Yang, Yutuo Liu, Shuai Zeng, Ziming Zhang, Yinlong Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China Shenyang University of Chemical Technology College of Information Engineering Shenyang110142 China Shenzhen Polytechnic School of Automotive and Transportation Engineering Shenzhen518055 China

ISBN: (纸本)9798350327182

The paper presents a machine learning approach to detect laminate gaps and to classify them as open or closed. Compared with the traditional detection methods, which suffer from low precision of point cloud segmentation and poor effect of gap extraction in traditional gap detection, this paper proposes a gap detection algorithm based on 3D Vision. First, an improved undirected graph point cloud segmentation algorithm is used to overcome the under-segmentation of the target region. Second, an adaptive vector for angle discriminant model is proposed to solve the problem of poor extraction effect of the gap edge points. Finally, the B-spline curve-fitting model is used to describe the 3D points on the lamination edges. The proposed algorithm has been evaluated in a visual quality detection platform for carbon fiber composite laminates. The results show that the proposed approach is able to accurately detect and classify laminate gaps in carbon fiber composite structures, providing a reliable tool for quality control in industrial manufacturing processes. © 2023 IEEE.

关键词： Extraction

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Research on Evasion Strategy of Aircraft Based on Deep Reinforcement Learning 14th

Research on Evasion Strategy of Aircraft Based on Deep Reinf...

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14th International Conference on Genetic and Evolutionary Computing, ICGEC 2021

作者： Li, Ye Zhang, Lin Wang, Kaixuan Zhang, Fuquan Fan, Yi China Academy of Launch Vehicle Technology Beijing100076 China Capital Aerospace Machinery Company Beijing100076 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China

ISBN: (纸本)9789811684296

In order to improve the autonomous penetration capability of aircraft, a method for generating aircraft maneuver avoidance strategies based on deep reinforcement learning is proposed. In order to solve the sparse reward problem of penetration reinforcement learning, the initialization process and sampling method of deep Q Network are improved, and the convergence efficiency of the learning algorithm is improved. Firstly, a penetration threat scene and an offensive and defensive confrontation motion model are established, and the relative motion state of the interceptor and the typical maneuver mode of the balanced flight section are selected as the state space and the action space. In the learning process, the aircraft is used as an agent to perform a reinforcement learning exploration process through confrontation simulations to train the maneuver value network so that it can finally make autonomous decisions based on the threat situation. Finally, the simulation experiment results show that the algorithm proposed in this paper can effectively generate maneuver penetration strategies and support the intelligent game of aircraft. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep learning

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