检索结果-内蒙古大学图书馆

Distributed Optimization and Scaling Design for Solving Sylvester Equations

Journal of Systems Science & Complexity 2024年第6期37卷 2487-2510页

作者： CHENG Songsong YU Xin ZENG Xianlin LIANG Shu HONG Yiguang Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and AutomationAnhui UniversityHefei 230601China Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Control Science and Engineering Tongji UniversityShanghai 201804China Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 201210China

This paper develops distributed algorithms for solving Sylvester *** authors transform solving Sylvester equations into a distributed optimization problem,unifying all eight standard distributed matrix *** the authors propose a distributed algorithm to find the least squares solution and achieve an explicit linear convergence *** results are obtained by carefully choosing the step-size of the algorithm,which requires particular information of data and Laplacian *** avoid these centralized quantities,the authors further develop a distributed scaling technique by using local information *** a result,the proposed distributed algorithm along with the distributed scaling design yields a universal method for solving Sylvester equations over a multi-agent network with the constant step-size freely chosen from configurable ***,the authors provide three examples to illustrate the effectiveness of the proposed algorithms.

关键词： Distributed optimization least squares solution linear convergence rate step-size interval Sylvester equation

来源：评论

学校读者我要写书评

暂无评论

Plant Disease Detection Using Machine Learning 4

Plant Disease Detection Using Machine Learning

引用

4th International Conference on Intelligent Technologies, CONIT 2024

作者： Parida, Amit Kumar Stonier, Albert Alexander Vit University School of Electrical Engineering Department of Control and Automation Vellore India Vellore Institute of Technology School of Electrical Engineering Vellore India

ISBN: (纸本)9798350349900

Plant diseases are a serious threat toworld agriculture, resulting in lower agricultural yields and financial losses. This study examines how machine learning methods could revolutionize the identification of plant diseases. The shortcomings of conventional approaches and suggest combining machine learning models with cutting-edge imaging and data processing technologies to improve the diagnosis's speed and precision. This research demonstrates how well machine learning methods, such as CNN and SVM, can distinguish between healthy and unhealthy plants. Also gone through how transfer learning can be used, especially when data is scarce, to modify previously trained models for illness detection. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

A Fractional Order Fast Repetitive control Paradigm of Vienna Rectifier for Power Quality Improvement

引用

computer Modeling in engineering & Sciences 2023年第2期134卷 1159-1176页

作者： Sue Wang Xintao Luo Saleem Riaz Haider Zaman Chaohong Zhou Pengfei Hao School of Electrical and Control Engineering Shaanxi University of Science and TechnologyXi’anChina School of Automation Northwestern Polytechnical UniversityXi’anChina Electronics Engineering Department University of Engineering and Technology PeshawarKhyberPakhtunKhwaPakistan

Due to attractive features,including high efficiency,low device stress,and ability to boost voltage,a Vienna rectifier is commonly employed as a battery charger in an electric vehicle(EV).However,the 6k±1 harmonics in the acside current of the Vienna rectifier deteriorate theTHDof the ac current,thus lowering the power ***,the current closed-loop for suppressing 6k±1 harmonics is essential tomeet the desired total harmonic distortion(THD).Fast repetitive control(FRC)is generally adopted;however,the deviation of power grid frequency causes delay link in the six frequency fast repetitive control to become non-integer and the tracking performance to *** paper presents the detailed parameter design and calculation of fractional order fast repetitive controller(FOFRC)for the non-integer delay *** finite polynomial approximates the non-integer delay link through the Lagrange interpolation *** comparing the frequency characteristics of traditional repetitive control,the effectiveness of the FOFRC strategy is ***,simulation and experiment validate the steadystate performance and harmonics suppression ability of FOFRC.

关键词： Vienna rectifier fast repetitive control fractional order performance analysis

来源：评论

学校读者我要写书评

暂无评论

Optimal Scheduling of an Independent Electro-Hydrogen System with Hybrid Energy Storage Using a Multi-Objective Standardization Fusion Method

引用

Energy engineering 2025年第1期122卷 63-84页

作者： Suliang Ma Zeqing Meng Mingxuan Chen Yuan Jiang School of Electrical and Control Engineering North China University of TechnologyBeijing100144China ChinaThree Gorges Technology Co. Ltd.Beijing100032China School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing100083China

In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is ***,it presents a challenge due to the significant deviations in values ofmultiple optimization objective functions caused by their physical *** deviations seriously affect the scheduling process.A novel standardization fusion method has been established to address this issue by analyzing the variation process of each objective function’s *** optimal scheduling results of IEHS with HESS indicate that the economy and overall energy loss can be improved 2–3 times under different optimization *** proposed method better balances all optimization objective functions and reduces the impact of their *** the cost of BESS decreases by approximately 30%,its participation deepens by about 1 ***,if the price of the electrolyzer is less than 15¥/kWh or if the cost of the fuel cell drops below 4¥/kWh,their participation will increase *** study aims to provide a more reasonable approach to solving multi-objective optimization problems.

关键词： Electro-hydrogen system multi-objective optimization standardization method hybrid energy storage system

来源：评论

学校读者我要写书评

暂无评论

Ontology-Based Semantic Reasoning for Multi-Source Heterogeneous Industrial Devices Using OPC UA

引用

IEEE Internet of Things Journal 2025年第13期12卷 25020-25032页

作者： Bi, Jing Wu, Rina Yuan, Haitao Wang, Ziqi Zhang, Jia Zhou, MengChu Beijing University of Technology College of Computer Science Beijing100124 China Beihang University School of Automation Science and Electrical Engineering Beijing China Southern Methodist University Department of Computer Science Lyle School of Engineering DallasTX75205 United States New Jersey Institute of Technology Department of Electrical and Computer Engineering NewarkNJ07102 United States

The advent of smart manufacturing in Industry 4.0 signifies the era of connections. As a communication protocol, Object linking and embedding for Process control Unified Architecture (OPC UA) can address most semantic heterogeneity issues. However, its semantics are not formally defined at the application layer. To address the information silo problem caused by semantic heterogeneity, an integration framework named Querying of Ontology Mapping-based OPC UA (QOMOU) is proposed. QOMOU extracts information models of OPC UA servers into resource description framework triples and utilizes web ontology language for semantic enrichment and inference. Then, an Event Class Semantic Similarity Calculation (ECSSC) method is proposed for device type identification, enabling the classification of semantically heterogeneous OPC UA devices. The effectiveness of ECSSC is validated through queries with the RDF query language (SPARQL) protocol in Apache Jena. Experimental results demonstrate that ECSSC improves the accuracy of device identification by approximately 7% compared to benchmark device identification models. Specifically, compared with graph embedding-based methods, QOMOU’s query performance is approximately 13% higher, and its query efficiency is 5% higher on average compared to both structured query and extensible markup languages. Moreover, by employing a keyword-matching algorithm, the query accuracy of the existing heterogeneous data integration scheme is improved by 4% on average. This enhancement can boost the operational efficiency of Internet of Things systems based on the OPC UA architecture. © 2014 IEEE.

关键词： Structured Query Language

来源：评论

学校读者我要写书评

暂无评论

Stability in Inverse Problem of Determining Two Parameters for the Moore-Gibson-Thompson Equation with Memory Terms

引用

Journal of Systems Science & Complexity 2024年第6期37卷 2368-2389页

作者： FU Songren CHEN Liangbiao ZHANG Ji-Feng Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Automation and Electrical Engineering Zhongyuan University of TechnologyZhengzhou 450007China

In this paper,the authors consider the inverse problem for the Moore-Gibson-Thompson equation with a memory term and variable diffusivity,which introduce a sort of delay in the dynamics,producing nonlocal effects in *** H¨older stability of simultaneously determining the spatially varying viscosity coefficient and the source term is obtained by means of the key pointwise Carleman estimate for the Moore-Gibson-Thompson *** the sake of generality in mathematical tools,the analysis of this paper is discussed within the framework of Riemannian geometry.

关键词： Carleman estimate memory term Moore-Gibson-Thompson equation stability Riemannian geometry

来源：评论

学校读者我要写书评

暂无评论

GRU combined model based on multi-objective optimization for short-term residential load forecasting

引用

Journal of Intelligent and Fuzzy Systems 2024年第4期46卷 10423-10440页

作者： Yi, Lingzhi Peng, Xinlong Fan, Chaodong Wang, Yahui Li, Yunfan Liu, Jiangyong College of Automation and Electronic Engineering Xiangtan University Hunan Engineering Research Center of Multi-energy Cooperative Control Technology Hunan Xiangtan China School of Computer Science and Technology Hainan University Hainan China College of Electrical and Information Engineering Hunan University Changsha China

Reliable and accurate short-term forecasting of residential load plays an important role in DSM. However, the high uncertainty inherent in single-user loads makes them difficult to forecast accurately. Various traditional methods have been used to address the problem of residential load forecasting. A single load forecast model in the traditional method does not allow for comprehensive learning of data characteristics for residential loads, and utilizing RNNs faces the problem of long-term memory with vanishing or exploding gradients in backpropagation. Therefore, a gated GRU combined model based on multi-objective optimization is proposed to improve the short-term residential load forecasting accuracy in this paper. In order to demonstrate the effectiveness, GRUCC-MOP is first experimentally tested with the unimproved model to verify the model performance and forecasting effectiveness. Secondly the method is evaluated experimentally with other excellent forecasting methods: models such as DBN, LSTM, GRU, EMD-DBN and EMD-MODBN. By comparing simulation experiments, the proposed GRU combined model can get better results in terms of MAPE on January, April, July, and November load data, so this proposed method has better performance than other research methods in short-term residential load forecasting. © 2024 - IOS Press. All rights reserved.

关键词： Multiobjective optimization

来源：评论

学校读者我要写书评

暂无评论

Segmented Real-time Dispatch Model and Stochastic Robust Optimization for Power-gas Integrated Systems with Wind Power Uncertainty

引用

Journal of Modern Power Systems and Clean Energy 2023年第5期11卷 1480-1493页

作者： Ying Wang Kaiping Qu Kaifeng Zhang Key Laboratory of Measurement and Control of CSE Ministry of EducationSchool of AutomationSoutheast UniversityNanjingChina School of Electrical Engineering China University of Mining and TechnologyXuzhouChina

This paper develops a segmented real-time dispatch model for power-gas integrated systems(PGISs), where power-to-gas(P2G) devices and traditional automatic generation control units are cooperated to manage wind power uncertainty. To improve the economics of the real-time dispatch in regard to the current high operation cost of P2Gs, the wind power uncertainty set is divided into several segments, and a segmented linear decision rule is developed, which assigns adjustment tasks differently when wind power uncertainty falls into different segments. Thus, the P2G operation with high costs can be reduced in real-time adjustment. Besides, a novel segmented stochastic robust optimization is proposed to improve the efficiency and robustness of PGIS dispatch under wind power uncertainty, which minimizes the expected cost under the empirical wind power distribution and builds up the security constraints based on the robust optimization. The expected cost is formulated using a Nataf conversion-based multi-point estimate method, and the optimal number of estimate points is determined through sensitivity analysis. Furthermore, a difference-ofconvex optimization with a partial relaxation rule is developed to solve the non-convex dispatch problem in a sequential optimization framework. Numerical simulations in two testing cases validate the effectiveness of the proposed model and solving method.

关键词： Power-gas integrated system robust optimization real-time dispatch multi-point estimate method differenceof-convex optimization

来源：评论

学校读者我要写书评

暂无评论

Vehicle and pedestrian detection method based on improved YOLOv4-tiny

引用

Optoelectronics Letters 2023年第10期19卷 623-628页

作者： LI Jing XU Zhengjun XU Liang School of Computer Science and Engineering Tianjin University of TechnologyTianjin300384China School of Electrical Engineering and Automation Tianjin University of TechnologyTianjin300384China

Aiming at the problem of low detection accuracy of vehicle and pedestrian detection models,this paper proposes an improved you only look once v4(YOLOv4)-tiny vehicle and pedestrian target detection *** block attention module(CBAM)is introduced into cross stage partial Darknet-53(CSPDarknet53)-tiny module to enhance feature extraction *** addition,the cross stage partial dense block layer(CSP-DBL)module is used to replace the original simple convolutional module superposition,which compensates for the high-resolution characteristic information and further improves the detection accuracy of the ***,the test results on the BDD100K traffic dataset show that the mean average precision(mAP)value of the final network of the proposed method is 88.74%,and the detection speed reaches 63 frames per second(FPS),which improves the detection accuracy of the network and meets the real-time detection speed.

关键词： replace network method

来源：评论

学校读者我要写书评

暂无评论

A deep convolutional neural network for COVID-19 detection using chest X-rays

引用

Research on Biomedical engineering 2022年第1期38卷 139-148页

作者： Bassi, Pedro R. A. S. Attux, Romis Department of Computer Engineering and Industrial Automation School of Electrical and Computer Engineering University of Campinas Campinas Brazil

Purpose: We present image classifiers based on Dense Convolutional Networks and transfer learning to classify chest X-ray images according to three labels: COVID-19, pneumonia, and normal. Methods: We fine-tuned neural networks pretrained on ImageNet and applied a twice transfer learning approach, using NIH ChestX-ray14 dataset as an intermediate step. We also suggested a novelty called output neuron keeping, which changes the twice transfer learning technique. In order to clarify the modus operandi of the models, we used Layer-wise Relevance Propagation (LRP) to generate heatmaps. Results: We were able to reach test accuracy of 100% on our test dataset. Twice transfer learning and output neuron keeping showed promising results improving performances, mainly in the beginning of the training process. Although LRP revealed that words on the X-rays can influence the networks’ predictions, we discovered this had only a very small effect on accuracy. Conclusion: Although clinical studies and larger datasets are still needed to further ensure good generalization, the state-of-the-art performances we achieved show that, with the help of artificial intelligence, chest X-rays can become a cheap and accurate auxiliary method for COVID-19 diagnosis. Heatmaps generated by LRP improve the interpretability of the deep neural networks and indicate an analytical path for future research on diagnosis. Twice transfer learning with output neuron keeping improved DNN performance. © 2021, Sociedade Brasileira de Engenharia Biomedica.

关键词： COVID-19

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：