检索结果-内蒙古大学图书馆

Frequency stability enhancement of a two-area interconnected power system under error-based active disturbance rejection control

引用

Measurement: Journal of the International Measurement Confederation 2025年 254卷

作者： Pang, Dawei Qin, Tianmu Du, Ming Niu, Yuguang State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing102206 China Beijing Huairou Laboratory Beijing101400 China

In the context of grid-connected renewable energy sources and deep peak shaving of thermal power units, the grid structure and characteristics are variable. In this regard, the application of error-based active disturbance rejection control (EADRC) in a two-area interconnected power system is considered with the aim of enhancing the frequency stability of the system. The stability of the proposed strategy is demonstrated and the effects of load variations and renewable energy output fluctuations on frequency are analyzed by modeling the two-area power system. Meanwhile, a comparison of control strategies of different orders is carried out. Simulation results show that the use of EADRC technique under NSGA-II rectification significantly improves the frequency response, both in terms of error and output smoothness. The effectiveness of the proposed strategy is verified in the IEEE 39-Bus system. The proper controller order selection and disturbance rejection core idea are beneficial to enhance the overall frequency stability of the power system. © 2025

关键词： Disturbance rejection

来源：评论

学校读者我要写书评

暂无评论

Multi-Timescale Optimal Operation Framework for Integrated Economic and Reliability Analysis of Hybrid Power Plants

Multi-Timescale Optimal Operation Framework for Integrated E...

引用

IEEE General Meeting Power& Energy Society

作者： Yuxin Deng Xin Fang Ningchao Gao Jin Tan Department of Electrical & Computer Engineering Mississippi State University Starkville MS USA Power System Engineering Center National Renewable Energy Laboratory Golden CO USA

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

This paper introduces a hierarchical modeling framework for hybrid power plants (HPP) to facilitate the operation of HPP in power systems similar to conventional generators (Congens) in the integrated multi-timescale optimal operation framework. To consider the uncertainties of HPP renewable power in the day-ahead scheduling, distributionally robust optimization (DRO) is used. To ensure that the state-of-charge (SOC) of energy storage systems in HPPs aligns closely with the planned value for long-term reliability, real-time SOC management is incorporated. In addition, an adjustable real-time control is designed for the robust delivery of HPP real-time services. Case studies performed on a revised IEEE 39-bus system demonstrate the effectiveness of the proposed framework for HPP operation. Simulation results highlight that the proposed framework not only can help operators schedule HPP similar to Congens in varying weather conditions but can also maintain the frequency reliability of the system.

关键词： Economics Uncertainty Real-time systems Hybrid power systems Stability analysis Power system reliability Reliability Power generation Meteorology Load modeling

来源：评论

学校读者我要写书评

暂无评论

CMD: A Cache-Assisted GPU Memory Deduplication Architecture

引用

IEEE Transactions on computer-Aided Design of Integrated Circuits and systems 2025年

作者： Zhao, Wei Feng, Dan Tong, Wei Wei, Xueliang Wu, Bing Ministry of Education of China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of data storage systems and Technology China

Massive off-chip accesses in GPUs are the main performance bottleneck. We find that many writes are duplicate, and the duplication can be inter-dup and intra-dup. While inter-dup means different memory blocks are identical, and intra-dup means all the 4B elements in a line are the same. In this work, we propose a cache-assisted GPU memory deduplication architecture named CMD to reduce the off-chip accesses via utilizing the data duplication in GPU applications. CMD includes three key design contributions which aim to reduce the three kinds of accesses: (1) A novel GPU memory deduplication architecture that removes the intra-dup and inter-dup lines. We design several techniques to manage duplicate blocks, reducing massive off-chip writes. (2) We propose a cache-assisted read scheme to reduce the reads to duplicate data. When an L2 cache miss wants to read the duplicate block, if the reference block has been fetched to L2 and it is clean, we can copy it to the L2 missed block without accessing off-chip DRAM. As for the reads to intra-dup data, CMD uses the on-chip metadata cache to get the data. (3) When a cache line is evicted, the clean sectors in the line are invalidated while the dirty sectors are written back. However, most read-only victims are re-referenced from DRAM more than twice. Therefore, we add a full-associate FIFO to accommodate the read-only (it is also clean) victims to reduce the re-reference counts. Experiments show that CMD can decrease the off-chip accesses by 31.01%, reduce the energy by 32.78% and improve performance by 42.53%. Besides, CMD can improve the performance of memory-intensive workloads by 57.56%. © 2025 IEEE.

关键词： Cache memory

来源：评论

学校读者我要写书评

暂无评论

Intelligent Blocking and Prevention of SARS-CoV-2 Based on Evolutionary Reinforcement Learning

Intelligent Blocking and Prevention of SARS-CoV-2 Based on E...

引用

Congress on Evolutionary Computation

作者： Chengwei He Huaping Hong Lijia Ma Qingling Zhu Yuan Bai College of Computer Science and Software Engineering Shenzhen University Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

In recent years, the global repercussions of SARS-CoV-2 and its variants have posed significant challenges to various areas, including the economic order, transportation, healthcare, and education, and the mitigation and prevention of SARS-CoV-2 and other infectious diseases have received much attention. This paper tries to develop a rational and effective intervention strategy in response to the dynamic evolution of the SARS-CoV-2 epidemic. To address this issue, we first use the SEIR model to analyze the population distribution under the SARS-CoV-2 epidemic, and then integrate a deep Q-neural network (DQN) to reflect an economic quantification model contextualized within the SARS-CoV-2 scenario. Next, we propose an evolutionary deep reinforcement learning to generate an optimal and adaptive intervention strategy, by optimizing the weight sequence of the DQN. The experimental results show the effectiveness of the proposed method in maximizing economic benefits, while ensuring the uninterrupted functionality of medical institutions. Importantly, the learned intervention strategy exhibits the applicability to other infectious diseases.

关键词： Economics Epidemics Infectious diseases Prevention and mitigation Heuristic algorithms Sociology Loss measurement

来源：评论

学校读者我要写书评

暂无评论

A Contribution to the Spatial Analysis of Territorial systems Based on Graph-Structured Data

A Contribution to the Spatial Analysis of Territorial System...

引用

Metrology for Living Environment (MetroLivEn), IEEE International Workshop on

作者： Simone Corrado Federico Romaniello Francesco Scorza School of Engineering Laboratory of Urban and Regional System Engineering (LISUT) University of Basilicata Potenza Italy Department of Mathematics Computer Science and Economics University of Basilicata Potenza Italy

ISBN: (数字)9798350385014

ISBN: (纸本)9798350385021

This work aims to present the methodological framework within which the T4Y project is developing as a contribution to the spatial analysis of complex systems related to tourism. The mapping of tourist ecosystems from a territorial perspective is a complex phenomenon due to the difficulty in understanding the interactions between tourists and the territory. Through the integration of AI-based techniques, the study aims to propose an approach based on graph-structured data to manage the complexity of geospatial information and improve planners' ability to abstract the possible relationships between elements of the territory. The approach utilizes graph-based data modeling while preserving spatial connections. It has been demonstrated how, through a bipartite graph approach, it is possible to decode the territorial components while taking into account the spatial connections between different pieces of information. Furthermore, the implementation of Graph Neural Networks (GNN) has been discussed as a way to facilitate a more integrated and context-aware analysis. This work aims to contribute to the ongoing debate on complex systems in spatial planning and provide valuable tools for policymakers and planners to experiment with scenarios for spatial development.

关键词： Ecosystems Metrology Graph neural networks Data models Planning Geospatial analysis Complexity theory

来源：评论

学校读者我要写书评

暂无评论

PAIR: protein-aptamer interaction prediction based on language models and contrastive learning framework

PAIR: protein-aptamer interaction prediction based on langua...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Jun Zhang Zhiqiang Yan Hao Zeng Zexuan Zhu National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Aptamers are single-stranded DNA or RNA oligonucleotides that selectively bind to specific targets, making them valuable for drug design and diagnostic applications. Identifying the interactions between aptamers and target proteins is crucial for these applications. The systematic evolution of ligands by exponential enrichment process, traditionally used for this purpose, is challenging and time-consuming. The resulting aptamers often suffer from limitations in stability and diversity. Computational approaches have shown promise in aiding the discovery of high-performance aptamers, but existing methods are usually constrained by insufficient training data and limited generalizability. Recently, advancements in pre-training large language models have offered a new avenue to mitigate the dependency on large datasets. In this study, we propose a novel method to predict aptamer-protein interactions using large language models within a contrastive learning framework. Experimental results demonstrate that our method exhibits superior generalization and outperforms existing approaches. This method holds promise as a powerful tool for predicting aptamer-protein interactions.

关键词： Proteins Drugs Protein engineering Biological system modeling Large language models Computational modeling Training data Contrastive learning Predictive models Few shot learning

来源：评论

学校读者我要写书评

暂无评论

High-integrated photonic tensor core utilizing high-dimensional lightwave and microwave multidomain multiplexing

引用

Light(Science & Applications) 2025年第1期14卷 227-237页

作者： Xiangyan Meng Nuannuan Shi Guojie Zhang Junshen Li Ye Jin Shiyou Sun Yichen Shen Wei Li Ninghua Zhu Ming Li Key Laboratory of Optoelectronic Materials and Devices Institute of SemiconductorsChinese Academy of SciencesBeijing100083China College of Materials Science and Opto-Electronic Technology University of Chinese Academy of SciencesBeijing100049China School of Electronic Electrical and Communication EngineeringUniversity of Chinese Academy of SciencesBeijing100049China China Academy of Space Technology(Xi’an) Xi’anShaanxi710100China WeChat Pay Lab 33 Shenzhen Tencent Computer System Co.Ltd.Shenzhen518054China Lightelligence Group Hangzhou311121China

The burgeoning volume of parameters in artificial neural network models has posed substantial challenges to conventional tensor computing *** from the available optical multidimensional information entropy,optical intelligent computing is used as an alternative solution to address the emerging challenges of electrical *** limitations,in terms of device size and photonic integration scale,have hindered the performance of optical ***,an ultrahigh computing density optical tensor processing unit(OTPU),which is grounded in an individual microring resonator(MRR),is introduced to respond to these *** the independent tuning of multiwavelength lasers,the operational capabilities of an MRR are orchestrated,culminating in the formation of an optical tensor *** design facilitates the execution of tensor convolution operations via the lightwave and microwave multidomain hybrid multiplexing in terms of the time,wavelength,and frequency of *** experimental results for the MRR-based OTPU show an extraordinary computing density of 34.04 TOPS/***,the achieved accuracy rate in recognizing MNIST handwritten digits was 96.41%.These outcomes signify a significant advancement toward the realization of high-performance optical tensor processing chips.

关键词： tuning resonator tensor

来源：评论

学校读者我要写书评

暂无评论

GAN-DIRNet:A Novel Deformable Image Registration Approach for Multimodal Histological Images

引用

computers, Materials & Continua 2024年第7期80卷 487-506页

作者： Haiyue Li Jing Xie Jing Ke Ye Yuan Xiaoyong Pan Hongyi Xin Hongbin Shen Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of ChinaShanghai200240China Department of Pathology Ruijin HospitalShanghai Jiao Tong UniversitySchool of MedicineShanghai200025China Department of Computer Science and Engineering Shanghai Jiao Tong UniversityShanghai200240China Global Institute of Future Technology Shanghai Jiao Tong UniversityShanghai200240China

Multi-modal histological image registration tasks pose significant challenges due to tissue staining operations causing partial loss and folding of *** neural network(CNN)and generative adversarial network(GAN)are pivotal inmedical image ***,existing methods often struggle with severe interference and deformation,as seen in histological images of conditions like Cushing’s *** argue that the failure of current approaches lies in underutilizing the feature extraction capability of the discriminator *** this study,we propose a novel multi-modal registration approach GAN-DIRNet based on GAN for deformable histological image *** begin with,the discriminators of two GANs are embedded as a new dual parallel feature extraction module into the unsupervised registration networks,characterized by implicitly extracting feature descriptors of specific ***,modal feature description layers and registration layers collaborate in unsupervised optimization,facilitating faster convergence and more precise ***,experiments and evaluations were conducted on the registration of the Mixed National Institute of Standards and Technology database(MNIST),eight publicly available datasets of histological sections and the Clustering-Registration-Classification-Segmentation(CRCS)dataset on the Cushing’s *** results demonstrate that our proposed GAN-DIRNet method surpasses existing approaches like DIRNet in terms of both registration accuracy and time efficiency,while also exhibiting robustness across different image types.

关键词： Histological images registration deformable registration generative adversarial network cushing’s disease machine learning computer vision

来源：评论

学校读者我要写书评

暂无评论

Propagation of transverse photonic orbital angular momentum through few-mode fiber

引用

Advanced Photonics 2023年第3期5卷 101-107页

作者： Qian Cao Zhuo Chen Chong Zhang Andy Chong Qiwen Zhan University of Shanghai for Science and Technology School of Optical-Electrical and Computer EngineeringShanghaiChina Zhangjiang Laboratory ShanghaiChina University of Shanghai for Science and Technology Shanghai Key Laboratory of Modern Optical SystemShanghaiChina Pusan National University Department of PhysicsBusanRepublic of Korea

Spatiotemporal optical vortex(STOV)pulses can carry transverse orbital angular momentum(OAM)that is perpendicular to the direction of pulse *** a STOV pulse,its spatiotemporal profile can be significantly distorted due to unbalanced dispersive and diffractive *** may limit its use in many research applications,where a long interaction length and a tight confinement of the pulse are *** first demonstration of STOV pulse propagation through a few-mode optical fiber is *** numerical and experimental analysis on the propagation of STOV pulse through a commercially available SMF-28 standard telecommunication fiber is *** spatiotemporal phase feature of the pulse can be well kept after the pulse propagates a few-meter length through the fiber even with *** propagation of the pulse will result in a breakup of its spatiotemporal spiral phase structure due to an excessive amount of modal group delay *** stable and robust transmission of transverse photonic OAM through optical fiber may open new opportunities for transverse photonic OAM studies in telecommunications,OAM lasers,and nonlinear fiber-optical research.

关键词： photonic orbital angular momentum spatiotemporal optical vortices multimode fiber

来源：评论

学校读者我要写书评

暂无评论

On the Selection of Intermediate Length Representative Periods for Capacity Expansion

On the Selection of Intermediate Length Representative Perio...

引用

IEEE General Meeting Power& Energy Society

作者： Osten Anderson Nanpeng Yu Konstantinos Oikonomou Di Wu Department of Electrical and Computer Engineering University of California Riverside Riverside CA System Evaluation Group Pacific Northwest National Laboratory Richland WA

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

As the decarbonization of power systems accelerates, there has been increasing interest in capacity expansion models for their role in guiding this transition. Representative period selection is an important component of capacity expansion modeling, enabling computational tractability of optimization while ensuring fidelity between the representative periods and the full year. However, little attention has been devoted to selecting representative periods longer than a single day. This prevents the capacity expansion model from directly simulating interday energy sharing, which is of key importance as energy generation becomes more variable and storage more important. To this end, we propose a novel method for selecting representative periods of any length. The method is validated using a capacity expansion model and production cost model based on California’s decarbonization goals. We demonstrate that the representative period length has a substantial impact in the results of the capacity expansion investment plan.

关键词： Renewable energy sources Costs Computational modeling Production Low carbon economy Linear programming Power systems Planning Optimization Investment

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：