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4th International Symposium on Insulation and Discharge Computation for Power Equipment, IDCOMPU 2023

作者： Cao, Jinxin Wang, Jianguo Du, Yaping Andreotti, Amedeo Ding, Yuxuan Cai, Li Fan, Yadong Zhou, Mi Engineering Research Center of Ministry of Education for Lightning Protection and Grounding Technology School of Electrical Engineering and Automation at Wuhan University Wuhan China Department of Building Energy and Environment Engineering The Hong Kong Polytechnic University Hong Kong Department of Electrical Engineering and Information Technology University of Naples Federico II Naples Italy

ISBN: (纸本)9789819974122

The complex distribution network has an obviously various lightning performance with that of the straight periodic lines, due to the uneven pole spans and feeder structure in the distribution network. In this paper, the lightning-induced flashover (FO) performance in a distribution network is investigated via a Monte Carlo method, based on the numerical PEEC-MTL method for line modeling and transient simulation. Different from the traditional indicator, i.e., the flashover rate of a total line, the annual FO number at individual poles is defined and concerned to reflect the distribution of the FO risk due to indirect lightning strikes. It is found that the in a part of an existing rural distribution network of concern if the terminal poles with distribution transformers located protected by surge arresters by default, the poles where the open area is around are more likely to have a higher annual FO number. The soil conductivity significantly affects the values of the annual FO number of individual poles, while there is no obvious change in its overall distribution characteristic of the distribution network, which is mainly determined by the line topology. Compared with the case without surge arresters besides the distribution transformers, it indicated the great significance of the protection for terminal poles with distribution transformers. The present work could provide a theoretical basis for differentiated protection against indirect lightning and more factors and conditions would be of concern in the following work. © Beijing Paike Culture Commu. Co., Ltd 2024.

关键词： Monte Carlo methods

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Improve Harris Hawkes optimizer algorithm via Laplace crossover

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Journal of Ambient Intelligence and Humanized Computing 2024年第4期15卷 2057-2072页

作者： Nasab, Seyed Taha Mousavi Abualigah, Laith Department of Applied Mathematics Iran University of Science and Technology Tehran Iran Computer Science Department Al al-Bayt University Mafraq25113 Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman19328 Jordan MEU Research Unit Middle East University Amman11831 Jordan Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon

Nowadays, the speed of solving optimization problems by increasing various issues and the number of variables is critical. The Harris Hawk optimization method is a brand-new, intelligent system that resolves optimization issues by mathematically simulating the natural behavior of hawks. In this study, the Harris Hawks optimization method and the Laplace crossover operator are merged, and a new enhanced Harris Hawks algorithm (LX-HHO) based on the Laplace optimization algorithm is suggested. The purpose of improving this algorithm is to increase the convergence speed while maintaining good accuracy in achieving the optimal solution. The results of the proposed method on the test functions demonstrate that the algorithm has achieved faster convergence than the original version of the Harris Hawks algorithm and other meta-heuristic algorithms. This is due to the algorithm's accuracy in obtaining the best answer in these functions and to a reduction in the evaluation of the optimization function. Also, comparing and evaluating the proposed algorithm with other algorithms by Friedman and MAE test shows the superiority of the LX-HHO algorithm. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Optimization

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Traffic Control Based on Integrated Kalman Filtering and Adaptive Quantized Q-Learning Framework for Internet of Vehicles

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computer Modeling in engineering & Sciences 2024年第3期138卷 2103-2127页

作者： Othman S.Al-Heety Zahriladha Zakaria Ahmed Abu-Khadrah Mahamod Ismail Sarmad Nozad Mahmood Mohammed Mudhafar Shakir Hussein Alsariera Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka(UTeM)Durian TunggalMalaysia College of Computing&Informatics Saudi Electronic UniversityRiyadhSaudi Arabia Department of Electrical Electronic and System EngineeringUniversiti Kebangsaan MalaysiaUKM BangiSelangorMalaysia Computer Technology Engineering College of Engineering TechnologyAl-Kitab UniversityKirkukIraq Faculty of Engineering and Electronic Engineering Universiti Tun Hussein Onn Malaysia(UTHM)Batu PahatMalaysia 6Research Center DepartmentThe University of MashreqBaghdadIraq

Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the *** this article,these issues are handled by proposing a novel framework for traffic control using vehicular communications and Internet of Things *** framework integrates Kalman filtering and *** smoothing Kalman filtering,our data fusion Kalman filter incorporates a process-aware model which makes it superior in terms of the prediction *** traditional Q-learning,our Q-learning algorithm enables adaptive state quantization by changing the threshold of separating low traffic from high traffic on the road according to the maximum number of vehicles in the junction *** evaluation,the model has been simulated on a single intersection consisting of four roads:east,west,north,and south.A comparison of the developed adaptive quantized Q-learning(AQQL)framework with state-of-the-art and greedy approaches shows the superiority of AQQL with an improvement percentage in terms of the released number of vehicles of AQQL is 5%over the greedy approach and 340%over the state-of-the-art ***,AQQL provides an effective traffic control that can be applied in today’s intelligent traffic system.

关键词： Q-learning intelligent transportation system(ITS) traffic control vehicular communication kalman filtering smart city Internet of Things

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Modeling of III-N heterostructures for GaN light-emitting diodes based on effective bond-orbital model 29

Modeling of III-N heterostructures for GaN light-emitting di...

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Light-Emitting Devices, Materials, and Applications XXIX 2025

作者： Hsiao, Fu-Chen Chang, Yia-Chung Wierer, Jonathan Kish, Fred Department of Electrical and Computer Engineering North Carolina State University RaleighNC27606 United States Research Center for Applied Sciences Academia Sinica Taipei11529 Taiwan

ISBN: (纸本)9781510685208

Spontaneous emission and Auger non-radiative recombination rates are critical factors influencing the performance of light-emitting diodes (LEDs). This study introduces a computational framework for evaluating both direct and phonon-assisted Auger recombination in III-Nitride (III-N) bulk materials and single quantum well (QW), leveraging the effective-bond orbital model (EBOM). The EBOM-derived band structure for Wurtzite III-N demonstrates excellent agreement with density functional theory calculations using the meta-generalized gradient approximation, affirming its efficiency and suitability for heterostructure systems due to its tight-binding-like orbital basis. Simulations reveal that the zone-center approximation for initial states is inadequate for accurate Brillouin zone integration in phonon-assisted Auger recombination calculations. The computational approach presented here can be generalized to study various indirect Auger recombination processes in heterostructures, including quantum wires and quantum dots. Incorporating refined electron-phonon matrix elements from advanced first-principles methods could further enhance result accuracy. Additionally, the calculated spontaneous emission rate in single InGaN/GaN QW is presented to provide a comprehensive perspective on GaN-based LEDs. The exciton states and corresponding enhancement factors are integrated into the spontaneous emission spectra, enabling accurate characterization of the dependence of LED spontaneous emission coefficients on carrier injection density. While this study focuses on calculating the Auger recombination rate, a comprehensive LED model based on EBOM, incorporating the present computational scheme, will be detailed in a forthcoming publication. © 2025 SPIE.

关键词： III-V semiconductors

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Cascading Delays for the High-Speed Rail Network Under Different Emergencies:A Double Layer Network Approach

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IEEE/CAA Journal of Automatica Sinica 2023年第10期10卷 2014-2025页

作者： Xingtang Wu Mingkun Yang Wenbo Lian Min Zhou Hongwei Wang Hairong Dong School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China School of Control and Computer Engineering North China Electric Power UniversityBeijing 100096China State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong UniversityBeijing 100044China National Research Center of Railway Safety Assessment Beijing Jiaotong UniversityBeijing 100044China

High-speed rail(HSR) has formed a networked operational scale in China. Any internal or external disturbance may deviate trains’ operation from the planned schedules, resulting in primary delays or even cascading delays on a network scale. Studying the delay propagation mechanism could help to improve the timetable resilience in the planning stage and realize cooperative rescheduling for dispatchers. To quickly and effectively predict the spatial-temporal range of cascading delays, this paper proposes a max-plus algebra based delay propagation model considering trains’ operation strategy and the systems’ constraints. A double-layer network based breadth-first search algorithm based on the constraint network and the timetable network is further proposed to solve the delay propagation process for different kinds of emergencies. The proposed model could deal with the delay propagation problem when emergencies occur in sections or stations and is suitable for static emergencies and dynamic emergencies. Case studies show that the proposed algorithm can significantly improve the computational efficiency of the large-scale HSR network. Moreover, the real operational data of China HSR is adopted to verify the proposed model, and the results show that the cascading delays can be timely and accurately inferred, and the delay propagation characteristics under three kinds of emergencies are unfolded.

关键词： Delay propagation double layer network high speed rail network max-plus algebra

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Indirect adaptive observer control (I-AOC) design for truck–trailer model based on T–S fuzzy system with unknown nonlinear function

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Complex and Intelligent Systems 2024年第5期10卷 7311-7331页

作者： Aslam, Muhammad Shamrooz Bilal, Hazrat Chang, Wer-Jer Yahya, Abid Badruddin, Irfan Anjum Kamangar, Sarfaraz Hussien, Mohamed Artificial Intelligence Research Institute China University of Mining and Technology Department of Automation University of Science and Technology of China Department of Marine Engineering of National Taiwan Ocean University (NTOU) Department of Electrical Computer and Telecommunications Engineering Botswana International University of Science and Technology Department of Mechanical Engineering College of Engineering King Khalid University Department of Chemistry Faculty of Science King Khalid University

Tracking is a crucial problem for nonlinear systems as it ensures stability and enables the system to accurately follow a desired reference signal. Using Takagi–Sugeno (T–S) fuzzy models, this paper addresses the problem of fuzzy observer and control design for a class of nonlinear systems. The Takagi–Sugeno (T–S) fuzzy models can represent nonlinear systems because it is a universal approximation. Firstly, the T–S fuzzy modeling is applied to get the dynamics of an observational system in order to estimate the unmeasurable states of an unknown nonlinear system. There are various kinds of nonlinear systems that can be modeled using T–S fuzzy systems by combining the input state variables linearly. Secondly, the T–S fuzzy systems can handle unknown states as well as parameters known to the indirect adaptive fuzzy observer. A simple feedback method is used to implement the proposed controller. As a result, the feedback linearization method allows for solving the singularity problem without using any additional algorithms. A fuzzy model representation of the observation system comprises parameters and a feedback gain. The Lyapunov function and Lipschitz conditions are used in constructing the adaptive law. This method is then illustrated by an illustrative example to prove its effectiveness with different kinds of nonlinear functions. A well-designed controller is effective and its performance index minimizes network utilization—this factor is particularly significant when applied to wireless communication systems. © The Author(s) 2024.

关键词： Adaptive observer control Feedback control design Indirect method Lyapunov–Krasovskii candidate T–S fuzzy models

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Discharge image reconstruction and frequency domain analysis based on event data

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High Voltage 2024年第6期9卷 1195-1201页

作者： Quan Yuan Lei Deng Hao Guo Qishen Lyu Xin Zhang Jibin Wu Yu Deng Hongyang Zhou Xilin Wang Zhidong Jia Engineering Laboratory of Power Equipment Reliability in Complicated Coastal Environments Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhenGuangdongChina Department of Precision Instrument Center for Brain Inspired Computing ResearchTsinghua UniversityBeijingChina College of Information and Computer Taiyuan University of TechnologyTaiyuanChina Shenzhen Power Supply Corporation China Southern Power Grid CorporationShenzhenChina Department of Computing The Hong Kong Polytechnic UniversityHong KongChina China Electric Power Research Institute BeijingChina School of Electrical Engineering and Automation Xiamen University of TechnologyXiamenChina

Optical image method has been the earliest and most used direct method for observing gas ***,research on gas discharge monitoring based on visible light mainly relies on high-speed cameras,but the large size,significant data storage requirements,and susceptibility to interference from complex backgrounds and lighting conditions limit their further *** vision sensing(DVS)technology is a neuromorphic sensing technology that asynchronously measures the luminance changes at each *** offers advantages such as a large dynamic range(>120 dB),high temporal resolution(up to 1µs),and small data volume(MB level).In this study,dynamic vision sensing technology was employed to monitor both 30 mm short-gaps and 1080 mm long-gaps discharge processes *** study developed the CountImage encoding method for event data and conducted image reconstruction,time-domain analysis,and frequency-domain charac-teristic analysis based on the event *** results show that the event-reconstructed images are highly consistent with the high-speed camera images,and the arc develop-ment process and its path can also be clearly ***,this study discovered a correlation between the electrical characteristics and event information during the discharge *** the time domain,the duration of the maximum DVS event count closely matches the duration during which the voltage drops to zero during *** the frequency domain,the Pearson correlation coefficient between the event stream spectrum and the voltage signal spectrum is greater than *** the maximum number of brightening events(ONmax)and the maximum number of darkening events(OFFmax)are positively correlated with the voltage applied between the *** study demonstrates that,compared to the GB/s data rate of high-speed cameras,this approach can record the discharge process and accurately reconstruct the discharge process,arc morphology,and discharge path at M

关键词： image analysis holds

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Cluster-HSFL: A Cluster-Based Hybrid Split and Federated Learning

Cluster-HSFL: A Cluster-Based Hybrid Split and Federated Lea...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Zhang, Songge Tu, Haoyu Li, Zuguang Liu, Shengbo Li, Shaofeng Wu, Wen Shen, Xuemin Sherman Peking University School of Electronic and Computer Engineering Shenzhen China Frontier Research Center Peng Cheng Laboratory Shenzhen China Department of Electrical and Computer Engineering Sun Yat-Sen University Guangzhou China Shenzhen China Department of Electrical and Computer Engineering University of Waterloo ON Canada

ISBN: (纸本)9798350345384

Federated learning (FL) and split learning (SL) are two machine learning paradigms that can distributedly train artificial intelligence (AI) models while guaranteeing client privacy. FL can parallelly train AI models based on clients' dataset, but it suffers from considerable communication overhead for model uploading and imposes a significant on-device computation workload. SL can mitigate the computation workload of the devices by offloading part of the AI model training to an edge server, but it suffers from long training delay for a large number of clients. To address these challenges, in this paper we present a cluster-based hybrid split federated learning (Cluster-HSFL) scheme by integrating FL and SL paradigms. This scheme can reduce training latency and alleviate on-device computational constraints while preserving accuracy performance. We establish a testbed for the Cluster-HSFL scheme based on the NVIDIA Jetson series hardware. The experimental results demonstrate that the Cluster-HSFL surpasses FL and SL by 6.3× and 1.8×, respectively, in terms of delay performance. Our results provide insight into the practical performance of the Cluster-HSFL scheme and can help guide future experimental research on SL in resource-limited wireless networks. © 2023 IEEE.

关键词： Artificial intelligence

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Optimized Home Appliance Scheduling Utilizing Reinforcement Learning for Enhanced Load Profile

Optimized Home Appliance Scheduling Utilizing Reinforcement ...

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2024 IEEE Middle East Conference on Communications and Networking, MECOM 2024

作者： Hassan, Eslam Al Abughali, Ahmed Alansari, Mohamad Muhaidat, Sami Khalifa University Department of Electrical Engineering and Computer Science Abu Dhabi United Arab Emirates Khalifa University 6G Research Center Department of Computer Science Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350376715

With the recent multiple increases in the fuel prices, and as most of electricity generation are fossil-fuelled, utilities were obliged to raise the electricity tariffs accordingly. Subsequently, individuals are compelled to reduce their energy usage to cut the daily energy bills. One approach to address this challenge is to enhance the overall efficiency of electrical systems by shifting peak demand periods, rather than relying on expanding the transmission network to correspond to peak demand indirectly. With the smart grid and deploying bi-directional smart meters, it is probable to perform load control using innovative Home Energy Management (HEM) systems with demand responseenabled appliances. A HEM system utilizes automated control and monitoring capabilities for household appliances, enabling it to make decisions regarding load shedding and shifting according to a predefined set of preferences. This in turn helps alleviate power system stress conditions and shift the peak demand. This study aims to develop two intelligent HEM systems with responseenabled appliances considering Reinforcement Learning (RL) as the main controlling algorithm and Time-of-Use (ToU) electricity price. The objective of the first controller is to minimize the power consumption while the second controller aims to enhance the load profile. The proposed RL-based intelligent HEM systems achieved 8.3% reduction and 1.25% for the minimization and load enhancement cases, respectively, achieving flexible appliance usage schedules that will minimize consumer energy bill without user lifestyle disruptions. © 2024 IEEE.

关键词： Reinforcement learning

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Formal Modeling of Road Network-Based Autonomous Vehicle Validation Scenarios With Intersections and Pedestrians

Formal Modeling of Road Network-Based Autonomous Vehicle Val...

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2024 IEEE International Performance, Computing, and Communications Conference, IPCCC 2024

作者： Kutlu, Ilke Goss, Quentin Akinci, Tahir Cetin Ilhan Akbas, Mustafa İstanbul Technical University Department of Electrical Engineering İstanbul Turkey Embry-Riddle Aeronautical University Department of Electrical Engineering and Computer Science FL United States University of California Riverside Center for Environmental Research and Technology RiversideCA United States

ISBN: (纸本)9798350367942

Autonomous vehicles (AVs) are an exciting emerging technology that reduces the active human participation in driving and extends awareness beyond human limitations of perception and reaction, increasing driving quality and safety. Validation testing of AVs provides the assurance of quality and safety, and is also an integral part of new AV research and development. Following in suite of their predecessor, i.e. non-autonomous vehicles, scenario-based validation testing is a safe, time and cost effective means of testing these complex, costly, and safety critical systems. In this paper we propose an open-source implementation of a scenario-based AV validation testing approach for AVs in traffic environments with pedestrians and intersections. Furthermore, we utilize the approach to implement scenarios of previously unimplementable AV scenarios from the Atomic Blocks dataset. © 2024 IEEE.

关键词： Automobile testing

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