检索结果-内蒙古大学图书馆

Impedance Modeling and Stability Analysis of a Three-phase Three-level NPC Inverter Connected to the Grid

CSEE Journal of Power and Energy systems 2020年第2期6卷 270-278页

作者： Bo Zhang Xiong Du Jingbo Zhao Jiapei Zhou Xiaoming Zou State Key Laboratory of Power Transmission Equipment&System Security and New Technology(Chongqing University) Shapingba DistrictChongqing 400044China Power System Technology Center Electric Power Research Institute of State GridJiangsu Electric Power Co.Ltd.Jiangsu 320115China HVDC Simulation Center Department of HVDC technologyGlobal Energy Interconnection Research InstituteBeijing 102209China

The interaction between grid-connected inverters and the grid may cause stability issues,and compromise the reliable operation of the *** study investigates the stability of a three-level neutral point clamped(NPC)inverter connected to the grid using impedance-based *** the impedance model of a three-phase three-level NPC inverter has not yet been reported,this study fills the literature gap by analyzing the influence of three-level DC-side neutral point control on the impedance *** fully considering the DC bus dynamics and DC voltage control loop,and the current loop and phase-locked loop(PLL),the admittance model of a three-phase three-level NPC inverter is established and verified by ***,in the stability analysis of a threelevel NPC inverter grid-connected system,the frequency coupling introduced by the PLL and DC bus dynamics is included with the help of an established admittance *** stability of the grid-connected system under different grid short circuit ratios(SCR)and operating power levels is analyzed according to the Nyquist stability *** experimental results revealed that the established impedance model of the three-phase three-level NPC inverter can properly represent the stability of this system.

关键词： Grid-connected inverter neutral point control stability three-level

来源：评论

学校读者我要写书评

暂无评论

Neuromodulated Meta-Learning

arXiv

引用

arXiv 2024年

作者： Wang, Jingyao Guo, Huijie Qiang, Wenwen Li, Jiangmeng Zheng, Changwen Xiong, Hui Hua, Gang University of Chinese Academy of Sciences Beijing China National Key Laboratory of Space Integrated Information System Institute of Software Chinese Academy of Sciences Beijing China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China Thrust of Artificial Intelligence Hong Kong University of Science and Technology Guangzhou China Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong Wormpex AI Research LLC BellevueWA98004 United States

Humans excel at adapting perceptions and actions to diverse environments, enabling efficient interaction with the external world. This adaptive capability relies on the biological nervous system (BNS), which activates different brain regions for distinct tasks. Meta-learning similarly trains machines to handle multiple tasks but relies on a fixed network structure, not as flexible as BNS. To investigate the role of flexible network structure (FNS) in meta-learning, we conduct extensive empirical and theoretical analyses, finding that model performance is tied to structure, with no universally optimal pattern across tasks. This reveals the crucial role of FNS in meta-learning, ensuring meta-learning to generate the optimal structure for each task, thereby maximizing the performance and learning efficiency of meta-learning. Motivated by this insight, we propose to define, measure, and model FNS in meta-learning. First, we define that an effective FNS should possess frugality, plasticity, and sensitivity. Then, to quantify FNS in practice, we present three measurements for these properties, collectively forming the structure constraint with theoretical supports. Building on this, we finally propose Neuromodulated Meta-Learning (NeuronML) to model FNS in meta-learning. It utilizes bi-level optimization to update both weights and structure with the structure constraint. Extensive theoretical and empirical evaluations demonstrate the effectiveness of NeuronML on various tasks. Code is publicly available at https://***/WangJingyao07/NeuronML. Copyright © 2024, The Authors. All rights reserved.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Eruption of a million-Kelvin warm magnetic flux rope on the Sun

arXiv

引用

arXiv 2024年

作者： Li, Leping Song, Hongqiang Peter, Hardi Chitta, Lakshmi Pradeep Cheng, Xin Li, Zhentong Zhou, Guiping National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Key Laboratory of Solar Activity and Space Weather National Space Science Center Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Shandong Provincial Key Laboratory of Optical Astronomy and Solar-Terrestrial Environment Institute of Space Sciences Shandong University Weihai Shandong264209 China Max Planck Institute for Solar System Research GöttingenD-37077 Germany School of Astronomy and Space Science Nanjing University Nanjing210093 China Key Laboratory of Dark Matter and Space Astronomy Purple Mountain Observatory Chinese Academy of Sciences Nanjing210023 China School of Astronomy and Space Science University of Science and Technology of China Hefei230026 China

Solar magnetic flux rope (MFR) plays a central role in the physics of coronal mass ejections (CMEs). It mainly includes a cold filament at typical chromospheric temperatures (∼10000 K) and a hot channel at high coronal temperatures (∼10MK). The warmMFR at quiescent coronal temperatures of a million Kelvin is, however, rarely reported. In this study, using multiwavelength images from Atmospheric Imaging Assembly (AIA) on board the Solar Dynamic Observatory (SDO) and Extreme Ultraviolet Imager (EUVI) on board the Solar Terrestrial Relations Observatory-A (STEREO-A), we present an eruption of a warm channel, that represents an MFR with quiescent coronal temperatures (∼0.6- 2.5MK). On 2022May 8, we observed the failed eruption of a hot channel, with the average temperature and emission measure (EM) of 10MK and 1.1×1028 cm-5, using AIA high-temperature images in active region (AR) 13007. This failed eruption was associated with a C8.2 flare, with no CME. Subsequently, we observed a warm channel that appeared in AIA and EUVI low-temperature images, rather than AIA high-temperature images. It then erupted, and transformed toward a semi-circular shape. An associated C2.1 flare, along with the signatures of magnetic reconnection in AIA high-temperature images, were identified. Additionally, we observed a CME associated with this event. Compared with the hot channel, the warm channel is cooler and rarer with the average temperature and EM of 1.7 (1.6) MK and 2.0×1026 (2.3×1026) cm-5. All the results suggest an unambiguous observation of the million-Kelvin warm MFR, that erupted as a CME, and fill a gap in the temperature domain of coronal MFRs. Copyright © 2024, The Authors. All rights reserved.

关键词： Magnetic flux

来源：评论

学校读者我要写书评

暂无评论

Visualization of the non-dominated solutions in many-objective optimization 4

Visualization of the non-dominated solutions in many-objecti...

引用

4th IEEE International Conference on Data science in Cyberspace, DSC 2019

作者： Xiong, Minghui Xiong, Wei Jian, Ping Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing101416 China

ISBN: (纸本)9781728145280

The high dimensionality of many-objective optimization makes it difficult to represent the relationships between objectives and solutions of such problems. The overlapping and visual confusion problems occur when mapping high-dimensional solution sets to two-dimensional planes in the conventional parallel coordinate plots, which adds difficulty for decision maker choosing a preference solution. This paper introduces a visualization method for many-objective optimization non-dominated solution sets based on fuzzy theory and electromagnetic field clustering. The fuzzy theory is used to classify the non-dominated solution set, and each rating grade denotes the preference degree of decision maker. Visual clustering is conducted by electromagnetic field clustering, the solutions in the same cluster attract each other while solutions between clusters are mutually exclusive. The distribution structure of preference solution is highlighted through brightness gradient enhancement to optimize the visual perception. The experimental results show that the visualization plot of the proposed method is more clear and intuitive than the original plot, which is convenient for decision makers to discover the pattern of solution sets and make final decisions. © 2019 IEEE.

关键词： Visualization

来源：评论

学校读者我要写书评

暂无评论

Structure characteristic-aware pruning strategy for convolutional neural networks 21

Structure characteristic-aware pruning strategy for convolut...

引用

21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data science and systems, HPCC/SmartCity/DSS 2019

作者： Zuo, Peixuan Wang, Rui Fu, Xianya Yang, Hailong Liu, Yi Zhang, Lianyi Zhang, Han Qian, Depei BeiHang University Beijing China Secience and Technology on Special System Simulation Laboratory Beijing China Beijing Simulation Center Beijing China

ISBN: (纸本)9781728120584

Convolutional Neural Networks have received considerable attention over the past few years, and they are widely used in various fields. However, the computational complexity and excessive storage space caused by over-parameterized of these networks are also being serious. This will limit further development of deep learning in resource-constrained devices such as the mobile terminal. It has been proposed that pruning is a useful method to optimize networks, whereas there is no contribution focus on utilizing the traits of the network to guide pruning. The primary purpose of this paper is to research the different effects of layers with varying depth and the different number of parameters during the pruning process. By taking advantage of the characteristics of network structure itself, we propose a new pruning strategy with three variants to effectively prune CNNs which can automatically determine the most appropriate sparsity for each conv-layer. Using iterative pruning and retraining, we evaluated our strategy on InceptionV3 and ResNet50. We analyzed our three variants and made a comparison between each other. © 2019 IEEE.

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

Technological Innovation as a Panacea to Rent-Seeking Behavior: How Can the Diffusion of Continuous Emissions Monitoring systems in Thermal Power Enterprises Be Promoted Based on an Evolutionary Game Model?

SSRN

引用

SSRN 2024年

作者： Wang, Yang Li, Dezhi Wei, Yigang Wang, Wentao Department of Construction and Real Estate School of Civil Engineering Southeast University Nanjing211189 China China-Pakistan Belt and Road Joint Laboratory on Smart Disaster Prevention of Major Infrastructures Ministry of Science and Technology Nanjing211189 China Engineering Research Center of Building Equipment Energy and Environment Ministry of Education Nanjing211189 China School of Economics and Management Beihang University Beijing100191 China Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operations Beijing100191 China Laboratory for Low-carbon Intelligent Governance Beihang University Beijing100191 China

Carbon data fraud caused by rent-seeking behavior (RSB) undermines the effectiveness of the Emissions Trading Scheme (ETS). The Continuous Emissions Monitoring system (CEMS) used for carbon monitoring is a powerful solution to this misconduct. This study aims to optimize regulatory measures for promoting CEMS and curbing RSB (PCaCR) to improve the robustness of ETS. A tripartite evolutionary game model was constructed based on strategic interactions among thermal power enterprises (TPEs), third-party verifiers (3PVs), and government. The Lyapunov indirect method was used to analyze evolutionary stabilization strategies (ESS). Numerical simulations were performed to assess the sensitivity of key factors. The empirical results indicate that, first, four scenarios of ESS for the stakeholders. The ideal ESS for the PCaCR is when TPEs apply CEMS for carbon monitoring, 3PVs impartially verify, and the government strictly supervises. Second, the initial strategy choices of stakeholders affect the time it takes for the game system to reach the ESS. The closer the initial strategy selection is to the ESS, the faster the evolution occurs. Third, factors with different sensitivities affects the evolutionary outcome and speed. Standard refinement, information disclosure, and reward & punishment mechanisms can regulate stakeholder decision-making. © 2024, The Authors. All rights reserved.

关键词： Carbon

来源：评论

学校读者我要写书评

暂无评论

Olivine-norite rock detected by the lunar rover Yutu-2 likely crystallized from the SPA-impact melt pool

引用

National science Review 2020年第5期7卷 913-920页

作者： Honglei Lin Zhiping He Wei Yang Yangting Lin Rui Xu Chi Zhang Meng-Hua Zhu Rui Chang Jinhai Zhang Chunlai Li Hongyu Lin Yang Liu Sheng Gou Yong Wei Sen Hu Changbin Xue Jianfeng Yang Jie Zhong Xiaohui Fu Weixing Wan Yongliao Zou Key Laboratory of Earth and Planetary Physics Institute of Geology and Geophysics Chinese Academy of Sciences Key Laboratory of Space Active Opto-Electronics Technology Shanghai Institute of Technical Physics Chinese Academy of Sciences State Key Laboratory of Lunar and Planetary Sciences Macau University of Science and Technology Beijing Institute of Space Mechanics and Electricity State Key Laboratory of Space Weather National Space Science CenterChinese Academy of Sciences State Key Laboratory of Remote Sensing Science Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Key Laboratory of Electronics and Information Technology for Space System National Space Science Center Chinese Academy of Sciences Xi'an Institute of Optics and Precision Mechanics Chinese Academy of Sciences Institute of Optics and Electronics Chinese Academy of Sciences Shandong Provincial Key Laboratory of Optical Astronomy and Solar-Terrestrial Environment Institute of Space SciencesShandong University

Chang’E-4 landed in the South Pole-Aitken (SPA) basin,providing a unique chance to probe the composition of the lunar *** landing site is located on ejecta strips in Von Karman crater that possibly originate from the neighboring Finsen crater.A surface rock and the lunar regolith at 10 sites along the rover Yutu-2 track were measured by the onboard Visible and Near-Infrared Imaging Spectrometer in the first three lunar days of mission *** situ spectra of the regolith have peak band positions at 1and 2μm,similar to the spectral data of Finsen ejecta from the Moon Mineralogy Mapper,which confirms that the regolith’s composition of the landing area is mostly similar to that of Finsen *** rock spectrum shows similar band peak positions,but stronger absorptions,suggesting relatively fresh *** rock may consist of 38.1±5.4%low-Ca pyroxene,13.9±5.1%olivine and 48.0±3.1%plagioclase,referred to as *** plagioclase-abundant and olivine-poor modal composition of the rock is inconsistent with the origin of the mantle,but representative of the lunar lower ***,the rock crystallized from the impact-derived melt pool formed by the SPA-impact event via mixing the lunar crust and mantle *** scenario is consistent with fast-cooling thermal conditions of a shallow melt pool,indicated by the fine to medium-sized texture (<3 mm) of the rock and the SPA-impact melting model[Icarus2012;220:730-43].

关键词： impact basin lunar interior composition visible and near-infrared spectra lunar rover Yutu-2 Chang’E-4 mission

来源：评论

学校读者我要写书评

暂无评论

Prediction of Direct Normal Irradiation Based on CNN-LSTM Model 20

Prediction of Direct Normal Irradiation Based on CNN-LSTM Mo...

引用

5th International Conference on Multimedia systems and Signal Processing, ICMSSP 2020

作者： Zhang, Chengying Yan, Zhen Ma, Chao Xu, Xiaoli Key Laboratory of Space Utilization Technology and Engineering Center for Space Utilization Chinese Academy of Sciences Beijing China Beijing Key Laboratory of Measurement and Control of Mechanical and Electrical System Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781450377485

Due to the intermittency and instability of power output of solar power stations (SPS), the safety and stationarity of the electric grid are facing considerable challenges. So, it is essential to predict the power output of SPS accurately. To date, as the most important meteorological factor determining the power output of SPS, the prediction of direct normal irradiation (DNI) has always been a hotspot, however at the same time a challenging problem. In recent years, with the improvement of hardware performance, deep learning methods have witnessed rapid development in the field of forecasting of renewable energies. In this paper, a hybrid method combining convolutional neural network (CNN) and longshort term memory (LSTM) neural network is proposed, the former can be effectively used for extraction of spatial feature, while the latter is used for extraction of temporal feature. As a case study, the proposed method is used for prediction of DNI of four typical days, i.e. spring equinox, summer solstice, autumn equinox, and winter solstice, based on the meteorological conditions of Zhangbei. The results show that deep learning methods can be effectively used for prediction of DNI, however, the proposed method in this paper achieves higher prediction accuracy than that of the compared methods. © 2020 ACM.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Learning-based high-speed single-pixel imaging using a cyclic random mask

引用

Optics Express 2025年第12期33卷 25728-25742页

作者： Shuoqi Lin Yichen Zhang Haofan Wang Zunwang Bo Fei Wang Guohai Situ School of Microelectronics Shanghai University Shanghai 200444 China Wangzhijiang Innovation Center for Laser Aerospace Laser Technology and System Department Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Shanghai 201800 China Key Laboratory of Space Laser Communication and Detection Technology Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Shanghai 201800 China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing 100049 China Shanghai Institute of Laser Technology Shanghai 200233 China ghsitu@***

Single-pixel imaging (SPI) is an advanced computational imaging technique that employs a simple bucket detector to capture object images without raster scanning. This method offers advantages such as low cost, high sensitivity, and suitability for imaging in low-light environments and specialized wavebands. However, SPI inherently suffers from a limitation in imaging speed due to the need to acquire intensity fluctuation signals under a large number of spatially modulated patterns. Here, we tackle this challenge by developing a high-speed optical modulation system and an advanced reconstruction algorithm, which together enhance the refresh rate of the optical modulation process while reducing the required sampling ratios, thereby enabling high-speed SPI. Specifically, on the hardware side, we implement a spinning disk modulation scheme with cyclic random patterns coded onto the disk, achieving a modulation refresh rate of 1 MHz. On the algorithmic side, we propose a physics-enhanced deep learning framework combined with a lightweight neural network, LiteUNet, which reduces the required sampling rate to 10%. By combining these innovations, we experimentally demonstrate high-speed SPI at 1926 fps with a spatial resolution of 71 × 73 pixels. This work offers an effective solution to address the imaging speed bottleneck in SPI, paving the way for its practical applications in fields such as microscopy and remote sensing.

关键词： Computational imaging Imaging techniques Optical systems Single pixel imaging Spatial light modulators Spatial resolution

来源：评论

学校读者我要写书评

暂无评论

嫦娥五号月壤中首次发现蒸发沉积成因的蓝辉铜矿

引用

science Bulletin 2023年第7期68卷 723-729页

作者：郭壮李琛李阳吴炎学朱晨曦文愿运法文哲李雄耀刘建忠欧阳自远 Institute of Remote Sensing and Geographical Information System School of Earth and Space SciencesPeking UniversityBeijing 100871China Center for Lunar and Planetary Sciences Institute of GeochemistryChinese Academy of SciencesGuiyang 550081China Faculty of Metallurgical and Energy Engineering Kunming University of Science and TechnologyKunming 650093China Center for Excellence in Comparative Planetology Chinese Academy of SciencesHefei 230026China Analysis and Test Center Guangdong University of TechnologyGuangzhou 510006China State Key Laboratory of High Performance Ceramics and Superfine Microstructures Shanghai Institute of CeramicsChinese Academy of SciencesShanghai 200050China

由于缺乏磁场和大气的保护,月球表面持续受到陨石和微陨石的轰击.撞击引起的气化沉积作用是月表典型的改造过程,该过程往往伴随独特矿物相的产生(如纳米金属铁以及铁硅化合物).研究团队通过对嫦娥五号月壤进行细致的扫描电子显微镜观察... 详细信息

由于缺乏磁场和大气的保护,月球表面持续受到陨石和微陨石的轰击.撞击引起的气化沉积作用是月表典型的改造过程,该过程往往伴随独特矿物相的产生(如纳米金属铁以及铁硅化合物).研究团队通过对嫦娥五号月壤进行细致的扫描电子显微镜观察,在纯铁颗粒以及玻璃质表面发现了具有典型气相沉积特征的含铜组分,进一步通过透射电子显微镜以及电子能量损失谱确认了这些含铜沉积物为蓝辉铜矿这是首次在月壤中发现此类矿物.本研究提供了月表硫化物发生气化沉积的直接证据,揭示了月表撞击过程引起的气相组分迁移及其对月表物质的显著改造效应.同时,嫦娥五号月壤中蓝辉铜矿的发现进一步拓宽了人们对月表复杂矿物组成的认识.

关键词： Vapor deposition Chang’e-5 lunar soil Digenite Impact ejecta

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：