检索结果-内蒙古大学图书馆

Solving dynamic optimization problems using parent–child multi-swarm clustered memory (PCSCM) algorithm

Neural Computing and Applications 2024年第31期36卷 19549-19583页

作者： Mohammadpour, Majid Mostafavi, Seyedakbar Mirjalili, Seyedali Department of Computer Engineering Yazd University Yazd Iran Center for Artificial Intelligence Research and Optimization Torrens University Australia Brisbane Australia Faculty of Electrical Engineering and Computer Science VŠB-TU Ostrava Czech Republic

The Particle Swarm Optimization (PSO) algorithm faces several inherent challenges when applied to dynamic and large-scale optimization problems. These challenges encompass the issues of outdated particle memory, inadequate scalability in high-dimensional search spaces, the incapability to detect environmental changes, a continual trade-off between exploration and exploitation, and the potential loss of population diversity within the problem space. To address these challenges, we propose a novel hybrid PSO algorithm, denoted as Parent–Child Multi-Swarm Clustered Memory (PCSCM). PCSCM is explicitly designed to leverage an enhanced memory system, capable of mitigating the issue of outdated particle memory after convergence, and efficiently adapting to changing environmental conditions. This innovative memory system retains and retrieves promising solutions from the past when environmental alterations occur. Additionally, PCSCM introduces clustering mechanisms for particles within each swarm, aimed at augmenting diversity within the problem space. This clustering strategy substantially bolsters the algorithm’s performance in tracking evolving optimal solutions and positively contributes to its scalability. Crucially, the clustering approach is implemented not only for the main population but also for stored solutions in memory, which collectively strike a balance between exploration and exploitation. In the proposed method, particle swarms are divided into parent and child swarms, with parent swarms dedicated to preserving diversity;while, child swarms focus on identifying local solutions. These clustering and memory strategies are consistently applied within each sub-swarm to effectively address the challenges posed by high-dimensional search spaces. In addition to addressing challenges related to dynamic optimization, our proposed Parent–Child Multi-Swarm Clustered Memory (PCSCM) algorithm introduces an innovative mechanism for detecting environmental changes. This n

关键词： Chaos theory

来源：评论

学校读者我要写书评

暂无评论

Diamagnetically Levitated and Trapped Graphite Mechanical Resonators 38

Diamagnetically Levitated and Trapped Graphite Mechanical Re...

引用

38th IEEE International Conference on Micro Electro Mechanical Systems, MEMS 2025

作者： Wang, Yunong Gage, Alexander Lee, Jaesung Feng, Philip X.-L. University of Florida Herbert Wertheim College of Engineering Department of Electrical and Computer Engineering GainesvilleFL32611 United States University of Central Florida College of Engineering & Computer Science Department of Electrical and Computer Engineering OrlandoFL32816 United States

ISBN: (纸本)9798331508890

We report on studying diamagnetic levitation and rigid body resonances of millimeter- to centimeter-scale trapped graphite mechanical resonators, by combining theoretical analysis with experimental demonstrations. Harnessing the strong diamagnetic susceptibility of pyrolytic graphite, we demonstrate stable levitation of square graphite thin plates with varying dimensions and masses above permanent magnets, without the need of active control. The resonance motions are excited by dielectric gradient forces and detected via an ultrasensitive optical interferometry system at room temperature. We observe rigid body resonance modes with frequencies between 25 Hz and 50 Hz and with their quality (Q) factors from 30 to 70. The Q factors are primarily constrained by air damping and eddy current damping. This work represents an initial step toward developing high-stability, anchor-less levitating resonant systems with large masses, paving the way for high-performance resonant sensors with minimal energy dissipation and exceptional thermal and mechanical isolation with very small power consumption. © 2025 IEEE.

关键词： Damping

来源：评论

学校读者我要写书评

暂无评论

Full-model-free Adaptive Graph Deep Deterministic Policy Gradient Model for Multi-terminal Soft Open Point Voltage Control in Distribution Systems

引用

Journal of Modern Power Systems and Clean Energy 2024年第6期12卷 1893-1904页

作者： Huayi Wu Zhao Xu Minghao Wang Youwei Jia Department of Electrical and Electronic Engineering The Hong Kong Polytechnic UniversityHong KongChina Shenzhen Research Institute The Hong Kong Polytechnic UniversityShenzhenChina Department of Electrical and Computer Engineering University of MacaoMacaoChina Department of Electrical and Electronic Engineering Southern University of Science and TechnologyShenzhenChina

High penetration of renewable energy sources(RESs)induces sharply-fluctuating feeder power,leading to volt-age deviation in active distribution *** prevent voltage violations,multi-terminal soft open points(M-sOPs)have been integrated into the distribution systems to enhance voltage con-trol ***,the M-SOP voltage control recalculated in real time cannot adapt to the rapid fluctuations of photovol-taic(PV)power,fundamentally limiting the voltage controllabili-ty of *** address this issue,a full-model-free adaptive graph deep deterministic policy gradient(FAG-DDPG)model is proposed for M-SOP voltage ***,the attention-based adaptive graph convolutional network(AGCN)is lever-aged to extract the complex correlation features of nodal infor-mation to improve the policy learning ***,the AGCN-based surrogate model is trained to replace the power flow cal-culation to achieve model-free ***,the deep deterministic policy gradient(DDPG)algorithm allows FAG-DDPG model to learn an optimal control strategy of M-SOP by continuous interactions with the AGCN-based surrogate *** tests have been performed on modified IEEE 33-node,123-node,and a real 76-node distribution systems,which demonstrate the effectiveness and generalization ability of the proposed FAG-DDPGmodel.

关键词： Soft open point graph attention graph convolutional network reinforcement learning voltage control distribution system deep deterministic policy gradient

来源：评论

学校读者我要写书评

暂无评论

The Development of Dental Problem Detection Device Using Inception V3 and Data Augmentation 8

The Development of Dental Problem Detection Device Using Inc...

引用

8th International Conference on electrical, Telecommunication and computer engineering, ELTICOM 2024

作者： Almodovar, Jacob P. Gloria, Germaine Beatrix A. Paglinawan, Charmaine C. School of Electrical Electronics and Computer Engineering Bachelor of Science in Electronics Engineering Manila Philippines

ISBN: (纸本)9798331531249

This study focuses on the development of a dental problem detection device using the Inception V3 deep learning model and advanced data augmentation techniques. Dental problems such as cavities, impacted wisdom teeth, and crowded teeth pose significant health risks, often requiring advanced imaging for accurate diagnosis. The proposed device utilizes an intraoral camera to capture digital tooth images, which are then processed using the Inception V3 model to identify three dental problems- dental caries, crowded teeth, and partially erupted wisdom teeth. By employing image data augmentation and leveraging datasets from various dental repositories, the study seeks to enhance the accuracy and reliability of dental diagnostics. As a result, the model achieved a total accuracy of 87.2%, in which the model attained a precision of 92%, a recall of 93%, and an Fl-score of 92.5% for caries detection. In detecting crowded teeth, it recorded a precision of 81.1 %, a recall of 90.9%, and an Fl-score of 85.7%. For partially erupted wisdom teeth detection, the precision was 88.8%, the recall 78%, and the Fl-score 83 %. These results indicate that while the model demonstrates strong overall performance, further improvements are necessary to improve the detection of crowded teeth and partially erupted wisdom teeth. This innovative approach endeavors to provide a non-invasive, efficient, and precise tool for dentists, potentially revolutionizing dental healthcare through the integration of advanced AI technologies into routine dental practices. © 2024 IEEE.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

Image-based Plant Diseases Detection using Deep Learning

引用

Materials Today: Proceedings 2023年 80卷 3500-3506页

作者： Panchal, Adesh V. Patel, Subhash Chandra Bagyalakshmi, K. Kumar, Pankaj Khan, Ihtiram Raza Soni, Mukesh Department of Computer Science & Engineering GEC Patan India School of Computer Science and Engineering VIT Bhopal University Sehore MP Bhopal India Electrical and Electronics Engineering SRI Ranganathar Institute of Engineering and Technology Coimbatore India Department of Computer Science & Engineering Institute of Engineering & Technology Uttar Pradesh Greater Noida India Jamia Hamdard Computer Science Department Delhi India Jagran Lakecity University Bhopal India

Agriculture plays a major role in developing countries like India, however the food security still remains a vital issue. Most of the crops get wasted due to lack of storage facility, transportation, and plant diseases. More than 15% of the crops get wasted in India due to diseases and hence it has become one of the major concern to be resolved. There is a need of automatic system that can identify these diseases and help farmers to take appropriate steps to get rid of crop loss. Farmers have followed the conventional method of identifying the plant disease with their naked eyes, and it not possible for all the farmers to identify these diseases the same way. With the advance in Artificial Intelligence, there is a need to incorporate the facilities of the computer vision in the field of agriculture. Deep Learning rich libraries and user as well as developer friendly environment to work with, all these qualities make Deep Learning as the favorable method to get started with this problem. In this paper we have used Deep Learning because of the advantages it offers to work with images especially in image classification to get improvised results. The methodology includes taking leaves of infected crops and label them as per the disease pattern. The images of infected leaves are processed pixel based operations are applied to improve the information from the image. As a next step feature extraction is done followed by image segmentation and at the last classification of crop diseases based on the patterns extracted from the diseased leaves. The CNN (Convolutional Neural Network) is used for the classification of diseases, for the demonstration purpose the public dataset is used consisting of around 87 K images (RGB type images) including healthy as well as diseased leaves. © 2021

关键词： Crops

来源：评论

学校读者我要写书评

暂无评论

Superior efficiency and stability of YbO_(x)-enhanced perovskite solar cells

引用

science China Materials 2024年第4期67卷 1356-1358页

作者： Qifeng Zhang Guozhong Cao Department of Electrical and Computer Engineering North Dakota State UniversityFargoND 58108-6050USA Department of Materials Science and Engineering University of WashingtonSeattleWA 98195-2120USA

Perovskite solar cells represent a revolutionary class of photovoltaic devices that have gained substantial attention for their exceptional performance and potential to provide an affordable and efficient solution for harnessing solar energy. These cells utilize perovskite-structured materials, typically hybrid organicinorganic lead halide compounds, as the light-absorbing layer.

关键词： energy perovskite stability

来源：评论

学校读者我要写书评

暂无评论

Multi-Period Resilient Model for VSC-Based AC-DC HDS Considering Public-Safety Power Shutoff to Mitigate Wildfires

引用

CSEE Journal of Power and Energy Systems 2024年第2期10卷 821-833页

作者： Zekai Wang Tao Ding Xiaosheng Zhang Chenggang Mu Pengwei Du Fangxing Li School of Electrical Engineering Xi'an Jiaotong UniversityXi'an 710049China Electric Reliability Council of Texas AustinTX76574 USA Department of Electrical Engineering and Computer Science The University of TennesseeKnoxville(UTK)TN37996USA

This paper proposes a voltage source converter (VSC) -based AC-DC hybrid distribution system (HDS) resilient model to mitigate power outages caused by wildfires. Before a wildfire happens, the public-safety power shutoff (PSPS) strategy is applied to actively cut some vulnerable lines which may easily cause wildfires, and reinforce some lines that are connected to critical loads. To mitigate load shedding caused by active line disconnection in the PSPS strategy, network reconfiguration is applied before the wildfire occurrence. During the restoration period, repair crews (RCs) repair faulted lines, and network reconfiguration is also taken into consideration in the recovery strategy to pick up critical loads. Since there exists possible errors in the wildfire prediction, several different scenarios of wildfire occurrence have been taken into consideration, leading to the proposition of a stochastic multi-period resilient model for the VSC-based AC-DC HDS. To accelerate the computational performance, a progressive hedging algorithm has been applied to solve the stochastic model which can be written as a mixed-integer linear program. The proposed model is verified on a 106-bus AC-DC HDS under wildfire conditions, and the result shows the proposed model not only can improve the system resilience but also accelerate computational speed.

关键词： AC-DC hybrid distribution system restoration network reconfiguration progressive hedging public safety power shutoffs strategy resilience

来源：评论

学校读者我要写书评

暂无评论

Transforming the electrical grid: the role of AI in advancing smart, sustainable, and secure energy systems

引用

Energy Informatics 2025年第1期8卷 1-43页

作者： Rajaperumal, T.A. Columbus, C. Christopher School of Electrical Engineering Vellore Institute of Technology Tamil Nadu Chennai India School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Chennai India

The evolution of the electrical grid from its early centralized structure to today’s advanced "smart grid" reflects significant technological progress. Early grids, designed for simple power delivery from large plants to consumers, faced challenges in efficiency, reliability, and scalability. Over time, the grid has transformed into a decentralized network driven by innovative technologies, particularly artificial intelligence (AI). AI has become instrumental in enhancing efficiency, security, and resilience by enabling real-time data analysis, predictive maintenance, demand-response optimization, and automated fault detection, thereby improving overall operational efficiency. This paper examines the evolution of the electrical grid, tracing its transition from early limitations to the methodologies adopted in present smart grids for addressing those challenges. Current smart grids leverage AI to optimize energy management, predict faults, and seamlessly integrate electric vehicles (EVs), reducing transmission losses and improving performance. However, these advancements are not without limitations. Present grids remain vulnerable to cyberattacks, necessitating the adoption of more robust methodologies and advanced technologies for future grids. Looking forward, emerging technologies such as Digital Twin (DT) models, the Internet of Energy (IoE), and decentralized grid management are set to redefine grid architectures. These advanced technologies enable real-time simulations, adaptive control, and enhanced human–machine collaboration, supporting dynamic energy distribution and proactive risk management. Integrating AI with advanced energy storage, renewable resources, and adaptive access control mechanisms will ensure future grids are resilient, sustainable, and responsive to growing energy demands. This study emphasizes AI’s transformative role in addressing the challenges of the early grid, enhancing the capabilities of the present smart grid, and shaping a secure

关键词： Risk management

来源：评论

学校读者我要写书评

暂无评论

Nanocryotron ripple counter integrated with a superconducting nanowire single-photon detector for megapixel arrays

引用

Physical Review Applied 2024年第2期22卷 024020-024020页

作者： Matteo Castellani Owen Medeiros Reed A. Foster Alessandro Buzzi Marco Colangelo Joshua C. Bienfang Alessandro Restelli Karl K. Berggren Electrical Engineering and Computer Science

Decreasing the number of cables that bring heat into the cryostat is a critical issue for all cryoelectronic devices. In particular, arrays of superconducting nanowire single-photon detectors (SNSPDs) could require more than 106 readout lines. Performing signal-processing operations at low temperatures could be a solution. Nanocryotrons, superconducting nanowire three-terminal devices, are good candidates for integrating sensing and electronics on the same technological platform as SNSPDs in photon-counting applications. In this work, we demonstrate that it is possible to read out, process, encode, and store the output of SNSPDs using exclusively superconducting nanowires patterned on niobium nitride thin films. In particular, we present the design and development of a nanocryotron ripple counter that detects input voltage spikes and converts the number of pulses to an N-digit value. The counting base can be tuned from 2 to higher values, enabling higher maximum counts without enlarging the circuit. As a proof of principle, we first experimentally demonstrate the building block of the counter, an integer-N frequency divider with N ranging from 2 to 5. Then, we demonstrate photon-counting operations at 405 nm and 1550 nm by coupling an SNSPD with a two-digit nanocryotron counter partially integrated on chip. The two-digit counter can operate in either base 2 or base 3, with a bit-error rate lower than 2×10−4 and a count rate of 107s−1. We simulate circuit architectures for integrated readout of the counter state and we evaluate the capabilities of reading out an SNSPD megapixel array that would collect up to 1012 counts per second. The results of this work, combined with our recent publications on a nanocryotron shift register and logic gates, pave the way for the development of nanocryotron processors, from which multiple superconducting platforms may benefit.

关键词： Cryogenic technology Optoelectronics Devices for digital logic, storage & processing Nanowires Optical sources & detectors Superconducting devices Microwave techniques Photon counting Single-photon detectors

来源：评论

学校读者我要写书评

暂无评论

Fair Probabilistic Multi-Armed Bandit With Applications to Network Optimization

IEEE Transactions on Machine Learning in Communications and ...

引用

IEEE Transactions on Machine Learning in Communications and Networking 2024年 2卷 994-1016页

作者： Guo, Zhiwu Zhang, Chicheng Li, Ming Krunz, Marwan The University of Arizona Department of Electrical and Computer Engineering TucsonAZ87521 United States The University of Arizona Department of Computer Science TucsonAZ85721 United States

Online learning, particularly Multi-Armed Bandit (MAB) algorithms, has been extensively adopted in various real-world networking applications. In certain applications, such as fair heterogeneous networks coexistence, multiple links (individual arms) are selected in each round, and the throughputs (rewards) of these arms depend on the chosen set of links. Additionally, ensuring fairness among individual arms is a critical objective. However, existing MAB algorithms are unsuitable for these applications due to different models and assumptions. In this paper, we introduce a new fair probabilistic MAB (FP-MAB) problem aimed at either maximizing the minimum reward for all arms or maximizing the total reward while imposing a fairness constraint that guarantees a minimum selection fraction for each arm. In FP-MAB, the learning agent probabilistically selects a meta-arm, which is associated with one or multiple individual arms in each decision round. To address the FP-MAB problem, we propose two algorithms: Fair Probabilistic Explore-Then-Commit (FP-ETC) and Fair Probabilistic Optimism In the Face of Uncertainty (FP-OFU). We also introduce a novel concept of regret in the context of the max-min fairness objective. We analyze the performance of FP-ETC and FP-OFU in terms of the upper bound of average regret and average constraint violation. Simulation results demonstrate that FP-ETC and FP-OFU achieve lower regrets (or higher objective values) under the same fairness requirements compared to existing MAB algorithms. © 2024 The Authors.

关键词： Wireless sensor 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：