检索结果-内蒙古大学图书馆

2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Amini, Shiva Golpîra, Hêmin Kamwa, Innocent Laval University Department of Electrical and Computer Engineering Canada University of Kurdistan Department of Electrical and Computer Engineering Iraq

ISBN: (纸本)9789531842976

In this paper, an advanced algorithm is presented that utilizes artificial neural networks (ANN) for estimating the inertia of synchronous generators (SGs). The algorithm is enhanced by integrating a modified equal area criterion method along with the kinetic energy concept to compute the maximum mechanical power (Pmax). This calculated Pmax is introduced as a novel input feature to the ANN model. Beyond the contributions already discussed, a supplementary proposal involves the development of a novel index designed to identify the most optimal fault location in power systems. The efficiency of the proposed algorithm was rigorously evaluated using simulations on the IEEE 39-bus New England test system. The simulation results demonstrated the algorithm's high accuracy, with an estimation error of less than 1% in determining the inertia of the generators. These findings underscore the algorithm's potential for enhancing the performance of power system stability analysis. © 2024 IEEE.

关键词： Power system analysis

来源：评论

学校读者我要写书评

暂无评论

Transistor-Level Metal Tube in Standard CMOS to Block Flying Crosstalk in BEOL Demonstrated in 38 GHz SPDT

IEEE Electron Device Letters

引用

IEEE Electron Device Letters 2025年第6期46卷 904-907页

作者： Hao, Weiquan Li, Xunyu Pan, Zijin Miao, Runyu Yue, Zijian Wang, Albert University of California Department of Electrical and Computer Engineering RiversideCA92521 United States

Analog, mixed-signal and radio-frequency (AMX/RF) integrated circuits (IC) are sensitive to noises and interferers. Such crosstalk is particularly problematic to complex chips in advanced technologies. Global flying noises coupling through complex metal interconnects in the backend-of-the-line (BEOL) in CMOS become dominant that cannot be isolated using traditional in-substrate noise-isolation techniques. This letter reports a novel layout-only transistor-level stacked-via metal tube structure in standard CMOS BEOL to suppress global flying noises on a chip. The new technique is validated in simulation and measurement using 38GHz single-pole double-throw (SPDT) traveling wave switch circuits fabricated in a foundry 45nm silicon-on-insulator (SOI) CMOS technology, demonstrating ~7 dB global noise reduction. © 1980-2012 IEEE.

关键词： CMOS integrated circuits

来源：评论

学校读者我要写书评

暂无评论

Guest Editorial: EV charging impacts on power system

引用

IET GENERATION TRANSMISSION & DISTRIBUTION 2024年第6期18卷 1091-1094页

作者： [Anonymous] Department of Electrical Engineering and Automation Aalto University Espoo Finland School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Department of Electrical Engineering São Paulo State University Ilha Solteira Brazil Electrical Engineering Department Sharif University of Technology Tehran Iran School of Industrial Engineering University of Castilla-La Mancha Ciudad Real Spain

来源：评论

学校读者我要写书评

暂无评论

Comparison of Two-Wheel and Four-Wheel Steering Using Event-Triggered Predictive Motion Control and Scale Vehicles

引用

ASME Letters in Dynamic Systems and Control 2024年第3期4卷 031002页

作者： Zhou, Zhaodong Rother, Christopher Chen, Jun Department of Electrical and Computer Engineering Oakland University RochesterMI48309 United States

This study compares the trajectory tracking performance of two- and four-wheel steering systems, especially under normal driving conditions. Specifically, the lateral motion is controlled by an event-triggered model predictive control (MPC), which activates either when consecutive control steps surpass the predictive horizon or when tracking error exceeds a predetermined lateral offset. Using a modified 1/10th scale Tamiya TT-02 RC car as a test platform, the tracking performance of both two- and four-wheel systems are evaluated. Results from the experiments highlight the better tracking performance of the four-wheel steering system over the traditional two-wheel systems and demonstrate the benefit of using event-triggered MPC for lateral motion control even under normal driving conditions, contrary to common belief that four-wheel steering systems are beneficial only in tight steering maneuvers. © 2024 by ASME.

关键词： Model predictive control

来源：评论

学校读者我要写书评

暂无评论

Digital Twin-Empowered Interference Management for Multi-hop Internet-of-Vehicles Networks Over Millimeter Wave Bands

引用

IEEE Internet of Things Journal 2025年第11期12卷 17807-17827页

作者： Elloumi, Mohamed Kaddoum, Georges Hassan, Md. Zoheb MontréalQC Canada Université Laval Electrical and Computer Engineering Department QC Canada

The Internet of Vehicles (IoV) generates massive data traffic and demands reliable end-to-end connectivity to achieve multi-Gbps throughput between vehicles and roadside units. Millimeter-wave (mmWave) bands, with their abundant bandwidth, are promising for high-throughput IoV networks. However, in this context, significant propagation losses, intermittent line-of-sight availability, and dynamic topology changes due to vehicle mobility present critical challenges. This paper introduces RAVEN (Resource Allocation for VEhicular Networks), a centralized resource management framework designed to address these challenges effectively. RAVEN leverages a digital twin network (DTN) to optimize the end-to-end system capacity of multi-hop mmWave IoV networks by effectively managing co-channel interference among vehicles. RAVEN comprises the following three steps: (i) a channel prediction step that utilizes DTN's awareness of vehicular mobility and environmental contexts to predict site-specific channel gains for vehicular communication links;(ii) a clustering step that partitions vehicles into non-overlapping clusters, allowing vehicles within each cluster to share the same mmWave channel for data transmission, while simultaneously reducing co-channel interference;(iii) a multi-hop connectivity optimization step that provides a connected vehicular networking topology by jointly optimizing vehicle-to-vehicle and vehicle-to-infrastructure connectivity using a graph theory approach. A proof-of-concept of RAVEN is developed by implementing a DTN on the Microsoft Azure Digital Twins platform while integrating real-world vehicular mobility traces, edge-cloud collaboration, and parallel computing. Extensive simulations demonstrate that RAVEN outperforms several benchmark schemes, and offers scalability and near real-time decision-making capabilities for managing interference in large-scale IoV networks. © 2014 IEEE.

关键词： Resource allocation

来源：评论

学校读者我要写书评

暂无评论

Energy-Efficient and Robust Communication in Multi-Connectivity Enabled mmWave Ultra-Dense Networks

IEEE Transactions on Green Communications and Networking

引用

IEEE Transactions on Green Communications and Networking 2024年第2期9卷 1-1页

作者： Kim, Jungjun Lee, Jihwan Bahk, Saewoong Department of Electrical and Computer Engineering and INMC Seoul National University Seoul Republic of Korea

The ultra-dense network (UDN) concept with multi-connectivity (MC) has emerged as a promising scenario for millimeter-wave (mmWave) communications due to its synergistic effect. However, mmWave UDNs with MC face challenges such as escalated energy consumption and computational complexity for traffic splitting decisions. To save energy and reduce the need for frequent traffic splitting decisions in the considered scenario, we formulate the problem as a mixed integer programming (MIP). Our objective is to determine which base stations (BSs) to enable for energy saving and how to split user traffic to maintain robust communication in MC enabled UDNs. To this end, this paper proposes energy-efficient and robust communication (), an ensemble of heuristic methods and convex optimization, to achieve our goal without directly solving the computationally expensive MIP. In addition, we consider greedy algorithm that potentially offers enhanced optimality. We analyze the complexity of each scheme and demonstrate that is the most viable option considering both performance and complexity. Through extensive simulations, we demonstrate that achieves over 98% optimality for small-sized networks. More importantly, we evaluate in realistic scenarios using a 3-D ray-tracing simulator and confirm that performs very well even in urban terrain environments with buildings. IEEE

关键词： Convex optimization

来源：评论

学校读者我要写书评

暂无评论

Exploration, Collaboration, and Applications in Multi-Agent Reinforcement Learning

引用

Performance Evaluation Review 2025年第3期52卷 31-34页

作者： Chen, Jingdi Department of Electrical and Computer Engineering Carnegie Mellon University PittsburghPA United States

In recent years, the field of humancentric decision-making has emerged as a critical area of research, driven by its potential to fundamentally reshape how decisions are made across a variety of complex systems. Human-centric decision-making is characterized by considerable variability, which can be both advantageous and problematic. Variability is beneficial in contexts like brainstorming or problem-solving, where diverse perspectives lead to innovation. However, in situations where consistency is crucial- such as public health, safety, and fairness-this variability can have negative consequences. For instance, when radiologists interpret the same mammogram differently, it can result in unnecessary medical procedures. Similarly, in military operations, inconsistent judgments by sonar technicians regarding potential threats can jeopardize both crew safety and mission success. This highlights the critical need for a deeper understanding of decisions where the stakes are high. Thus, it is important to deepen our understanding of the decision-making process in completed and dynamic scenarios that involve multiple decisionmakers. This should guide the creation of validated methods to identify, measure, model, and adjust variability in judgments to improve decision-making in multi-agent environments. © 2025 Copyright is held by the owner/author(s).

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

RIS-Assisted Integrated Sensing and Communication Systems: Joint Reflection and Beamforming Design

IEEE Open Journal of the Communications Society

引用

IEEE Open Journal of the Communications Society 2024年 5卷 908-927页

作者： Ismail, Mohamed I. Shaheen, Abdullah M. Fouda, Mostafa M. Alwakeel, Ahmed S. Modern Academy for Engineering and Technology Department of Electronic Engineering and Communication Technology Cairo4410242 Egypt Suez University Faculty of Engineering Department of Electrical Engineering Suez8151650 Egypt Idaho State University College of Science and Engineering Department of Electrical and Computer Engineering PocatelloID83209 United States

The Integrated Sensing and Communication (ISAC) system merged with Reconfigurable Intelligent Surface (RIS) has recently received much attention. This paper proposes an intelligent metaheuristic version of Enhanced Artificial Ecosystem Optimizer (EAEO) for a suggested beamforming optimization framework in ISAC systems with RIS. Two RIS are utilized in the presented model to enhance the received signal-to-noise ratio (SNR) for multiple-input multiple-output (MIMO) communication systems. Also, each element of each RIS scatters the incoming signal with a controllable phase-shift, without increasing its power. The signal is transmitted by a Dual-Function Base Station (DFBS) that is integrated with the RIS, which performs both communication and sensing functions simultaneously. The ISAC system is designed to optimize the signal transmission through the RIS by maximizing the SNR to increase the overall performance. In the proposed EAEO version, a Fitness-Distance-Balance Model (FDBM) is combined with the standard Artificial Ecosystem Optimizer (AEO) to improve the quality of the solutions in multidimensional and nonlinear optimization scenarios. The simulation results show that the proposed EAEO algorithm improves the SNR of different users for different numbers of RIS elements. The SNR reaches 25 dB when using 200 RIS elements. Moreover, the proposed EAEO is tested on the IEEE Congress on Evolutionary Computation 2017 (IEEE CEC'17) test suite. A comparative analysis is conducted compared to the standard AEO and several recent algorithms. The proposed EAEO derives great effectiveness and robustness over the others as it provides a higher rate of success in achieving the global optimum point. © 2020 IEEE.

关键词： Signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

Optimized Temporary Frequency Support for Wind Power Plants Considering Expanded Operational Region of Wind Turbines

引用

CSEE Journal of Power and Energy Systems 2025年第1期11卷 51-64页

作者： Zhengyang Hu Bingtuan Gao Zhao Xu Sufan Jiang School of Electrical Engineering Southeast UniversityNanjing210096China Department of Electrical and Electronic Engineering The Hong Kong Polytechnic UniversityHong Kong SARChina Department of Electrical Engineering and Computer Science The University of TennesseeKnoxvilleTN 37996 USA

Wind power plants(WPPs)are increasingly mandated to provide temporary frequency support to power systems during contingencies involving significant power ***,the frequency support capabilities of WPPs under derated operations remain insufficiently investigated,highlighting the potential for further improvement of the frequency *** paper proposes a bi-level optimized temporary frequency support(OTFS)strategy for a *** implementation of the OTFS strategy is collaboratively accomplished by individual wind turbine(WT)controllers and the central WPP ***,to exploit the frequency support capability of WTs,the stable operational region of WTs is expanded by developing a novel dynamic power control approach in WT *** approach synergizes the WTs'temporary frequency support with the secondary frequency control of synchronous generators,enabling WTs to release more kinetic energy without causing a secondary frequency ***,a model predictive control strategy is developed for the WPP *** strategy ensures that multiple WTs operating within the expanded stable region are coordinated to minimize the magnitude of the frequency drop through efficient kinetic energy ***,comprehensive case studies are conducted on a real-time simulation platform to validate the effectiveness of the proposed strategy.

关键词： Active power control model predictive control optimized temporary frequency support wind power plant wind turbine

来源：评论

学校读者我要写书评

暂无评论

CTRL: Clustering Training Losses for Label Error Detection

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第8期5卷 4121-4135页

作者： Yue, Chang Jha, Niraj K. Princeton University Department of Electrical and Computer Engineering PrincetonNJ08540 United States

In supervised machine learning, use of correct labels is extremely important to ensure high accuracy. Unfortunately, most datasets contain corrupted labels. Machine learning models trained on such datasets do not generalize well. Thus, detecting the label errors can significantly increase their efficacy. We propose a novel framework, called CTRL11CTRL is open-source: https://***/chang-yue/ctrl. (Clustering TRaining Losses for label error detection), to detect label errors in multiclass datasets. It detects label errors in two steps based on the observation that models learn clean and noisy labels in different ways. First, we train a neural network (NN) using the noisy training dataset and obtain the loss curve for each sample. Then, we apply clustering algorithms to the training losses to group samples into two categories: cleanly labeled and noisily labeled. After label error detection, we remove samples with noisy labels and retrain the model. Our experimental results demonstrate state-of-the-art error detection accuracy on both image and tabular datasets under labeling noise. We also use a theoretical analysis to provide insights into why CTRL performs so well. © 2020 IEEE.

关键词： Neural networks

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：