检索结果-内蒙古大学图书馆

3rd International Conference on Advanced Electrical Engineering, ICAEE 2024

作者： Aoumri, Mohammed Harrouz, Abdelkader Yaichi, Ibrahim Baala, Seddik Wira, Patrice University of Ahmed Draïa Adrar Algeria Institute for Research in Computer Science Mathematics Automation and Signal University of Haute Alsace Mulhouse France

ISBN: (纸本)9798350349351

Wind energy has emerged as an increasingly viable renewable energy source, driven by rising fossil fuel costs, energy security concerns, and environmental considerations. In 2022, wind energy production grew by 9% compared to 2021, maintaining an annual rate exceeding 12% since 2012. This study focuses on the application of Field Oriented Control (FOC), a prevalent control strategy in wind power generation systems, to a permanent magnet synchronous generator (PMSG) in a variable speed wind turbine configuration. The research methodology involved implementing FOC and conducting robustness analyses through PMSG parameter variations. The primary objectives were to maximize wind energy capture efficiency while ensuring sustained control performance. MATLAB/Simulink was employed to simulate and evaluate the various components of the wind turbine system (WTS), facilitating comprehensive analysis of the results. © 2024 IEEE.

关键词： Windmill

来源：评论

学校读者我要写书评

暂无评论

Approximation Schemes for Geometric Knapsack for Packing Spheres and Fat Objects 51

Approximation Schemes for Geometric Knapsack for Packing Sph...

引用

51st International Colloquium on Automata, Languages, and Programming, ICALP 2024

作者： Acharya, Pritam Bhore, Sujoy Gupta, Aaryan Khan, Arindam Mondal, Bratin Wiese, Andreas Department of Mathematics Indian Institute of Science Education and Research Pune India Department of Computer Science and Engineering Indian Institute of Technology Bombay India Department of Computer Science and Automation Indian Institute of Science Bengaluru India Department of Mathematics Technical University of Munich Germany

ISBN: (纸本)9783959773225

We study the geometric knapsack problem in which we are given a set of d-dimensional objects (each with associated profits) and the goal is to find the maximum profit subset that can be packed non-overlappingly into a given d-dimensional (unit hypercube) knapsack. Even if d = 2 and all input objects are disks, this problem is known to be NP-hard [Demaine, Fekete, Lang, 2010]. In this paper, we give polynomial time (1 + Ε)-approximation algorithms for the following types of input objects in any constant dimension d: disks and hyperspheres, a class of fat convex polygons that generalizes regular k-gons for k ≥ 5 (formally, polygons with a constant number of edges, whose lengths are in a bounded range, and in which each angle is strictly larger than π/2), arbitrary fat convex objects that are sufficiently small compared to the knapsack. We remark that in our PTAS for disks and hyperspheres, we output the computed set of objects, but for a OΕ(1) of them we determine their coordinates only up to an exponentially small error. However, it is not clear whether there always exists a (1 + Ε)-approximate solution that uses only rational coordinates for the disks’ centers. We leave this as an open problem which is related to well-studied geometric questions in the realm of circle packing. © Pritam Acharya, Sujoy Bhore, Aaryan Gupta, Arindam Khan, Bratin Mondal, and Andreas Wiese.

关键词： Approximation algorithms

来源：评论

学校读者我要写书评

暂无评论

Cubature Kalman Fusion Filtering Under Amplify-and-Forward Relays With Randomly Varying Channel Parameters

引用

IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 356-368页

作者： Jiaxing Li Zidong Wang Jun Hu Hongli Dong Hongjian Liu the Department of Applied Mathematics Harbin University of Science and Technology IEEE the Department of Computer Science Brunel University London the School of Automation Harbin University of Science and Technology the Artificial Intelligence Energy Research Institute Northeast Petroleum University the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum University the National Key Laboratory of Continental Shale Oil of China Northeast Petroleum University the Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of Education Anhui Polytechnic University the School of Mathematics and Physics Anhui Polytechnic University

In this paper, the problem of cubature Kalman fusion filtering(CKFF) is addressed for multi-sensor systems under amplify-and-forward(AaF) relays. For the purpose of facilitating data transmission, AaF relays are utilized to regulate signal communication between sensors and filters. Here, the randomly varying channel parameters are represented by a set of stochastic variables whose occurring probabilities are permitted to exhibit bounded uncertainty. Employing the spherical-radial cubature principle, a local filter under AaF relays is initially constructed. This construction ensures and minimizes an upper bound of the filtering error covariance by designing an appropriate filter gain. Subsequently, the local filters are fused through the application of the covariance intersection fusion rule. Furthermore, the uniform boundedness of the filtering error covariance's upper bound is investigated through establishing certain sufficient conditions. The effectiveness of the proposed CKFF scheme is ultimately validated via a simulation experiment concentrating on a three-phase induction machine.

关键词： Amplify-and-forward (AaF) relays covariance intersection fusion cubature Kalman filtering multi-sensor systems uniform boundedness

来源：评论

学校读者我要写书评

暂无评论

Maximum Power Point Tracking for PV Systems: A Comparison of Perturb & Observe and Fuzzy Logic Control 11

Maximum Power Point Tracking for PV Systems: A Comparison of...

引用

11th International Conference on ENERGY and ENVIRONMENT, CIEM 2023

作者： Tahiri, Fadila Hartani, M. Amine Harrouz, Abdelkader Dumbrava, Virgil Wira, Patrice Technology and Sciences Department LDDI Laboratory Adrar Algeria Department of Hydrocarbon and Renewable Energy LDDI Laboratory Adrar Algeria Department of Electric Power Systems Polytechnic University of Bucharest Bucharest Romania Institute for Research in Computer Science Mathematics Automation and Signal Mulhouse France

ISBN: (纸本)9798350340785

The purpose of this research paper is to explore different approaches to maximize power point tracking (MPPT) in photovoltaic (PV) systems. In this work, we evaluate and compare incremental conductance (InC) and fuzzy logic control techniques. To extract the highest amount of power, a DC/DC boost converter is employed between the PV system and the load. Traditional MPPT techniques like InC have demonstrated limitations in effectively identifying and precisely tracking the highest peak, leading to significant power losses, Therefore, a proposed approach called fuzzy logic control is recommended, which provides several advantages including robustness against parameter variations, minimal distortion in current output, and superior reference tracking. Simulation results conducted in MATLAB confirm that the suggested control method effectively reduces steady-state fluctuations and achieves improved tracking of the maximum power point with reduced power losses compared to InC control. ©2023 IEEE.

关键词： Fuzzy logic

来源：评论

学校读者我要写书评

暂无评论

Industrial Control Anomaly Detection Based on Distributed Linear Deep Learning

引用

computers, Materials & Continua 2025年第1期82卷 1129-1150页

作者： Shijie Tang Yong Ding Huiyong Wang School of Computer Science and Information Security Guilin University of Electronic TechnologyGuilin541004China School of Electronic Engineering and Automation Guilin University of Electronic TechnologyGuilin541004China Guangxi Engineering Research Center of Industrial Internet Security and Blockchain Guilin University of Electronic TechnologyGuilin541004China Institute of Cyberspace Technology HKCT Institute for Higher EducationHong Kong999077China School of Mathematics&Computing Science Guilin University of Electronic TechnologyGuilin541004China

As more and more devices in Cyber-Physical Systems(CPS)are connected to the Internet,physical components such as programmable logic controller(PLC),sensors,and actuators are facing greater risks of network attacks,and fast and accurate attack detection techniques are *** key problem in distinguishing between normal and abnormal sequences is to model sequential changes in a large and diverse field of time *** address this issue,we propose an anomaly detection method based on distributed deep *** method uses a bilateral filtering algorithm for sequential sequences to remove noise in the time series,which can maintain the edge of discrete *** use a distributed linear deep learning model to establish a sequential prediction model and adjust the threshold for anomaly detection based on the prediction error of the validation *** method can not only detect abnormal attacks but also locate the sensors that cause *** conducted experiments on the Secure Water Treatment(SWAT)and Water Distribution(WADI)public *** experimental results show that our method is superior to the baseline method in identifying the types of attacks and detecting efficiency.

关键词： Anomaly detection CPS deep learning MLP(multi-layer perceptron)

来源：评论

学校读者我要写书评

暂无评论

Multiobjective adaptive car-following control of an intelligent vehicle based on receding horizon optimization

引用

science China(Information sciences) 2023年第4期66卷 301-302页

作者： Hongbo GAO Juping ZHU Fei ZHANG Ruidong YAN Junjie ZHOU Lei JIANG Jianqiang WANG Keqiang LI Department of Automation University of Science and Technology of China Institute of Advanced Technology University of Science and Technology of China Department of Computational Mathematics School of Mathematical Sciences Anhui University School of Traffic and Transportation Beijing Jiaotong University Autonomous Driving Business Unit Chery Automobile School of College of Computer Science and Technology Zhejiang University China North Vehicle Research Institute School of Automotive Engineering Tsinghua University

Dear editor, Vehicle control is one of the key steps of intelligent driving [1]. Algorithms based on receding horizon optimization(RHO) can predict future trajectories and handle multiobjective constraint conditions; therefore, RHO-based methods have attracted considerable attention in the field of vehicle control. Although existing methods use RHO to design controllers, they do not simultaneously meet the multiobjective optimal control performance requirements on tracking, fuel economy, and ride comfort.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Preventing Cloud Network from Spamming Attacks Using Cloudflare and KNN

引用

computers, Materials & Continua 2023年第2期74卷 2641-2659页

作者： Muhammad Nadeem Ali Arshad Saman Riaz SyedaWajiha Zahra Muhammad Rashid Shahab S.Band Amir Mosavi Department of Computer Science Abasyn UniversityIslamabad44000Pakistan Department of Computer Science National University of TechnologyIslamabad44000Pakistan Future Technology Research Center National Yunlin University of Science and TechnologyDouliuYunlin64002Taiwan Institute of Information Society University of Public ServiceBudapest1083Hungary John von Neumann Faculty of Informatics Obuda UniversityBudapestHungary Institute of Information Engineering Automation and MathematicsSlovak University of Technology in BratislavaSlovakia

Cloud computing is one of the most attractive and cost-saving models,which provides online services to *** computing allows the user to access data directly from any *** nowadays,cloud security is one of the biggest issues that *** types of malware are wreaking havoc on the *** on the cloud server are happening from both internal and external *** paper has developed a tool to prevent the cloud server from spamming *** an attacker attempts to use different spamming techniques on a cloud server,the attacker will be intercepted through two effective techniques:Cloudflare and K-nearest neighbors(KNN)*** will block those IP addresses that the attacker will use and prevent spamming ***,the KNN classifiers will determine which area the spammer belongs *** the end of the article,various prevention techniques for securing cloud servers will be discussed,a comparison will be made with different papers,a conclusion will be drawn based on different results.

关键词： Intrusion prevention system spamming KNN classification spam cyber security botnet

来源：评论

学校读者我要写书评

暂无评论

research on Path Planning of Mobile Robot Based on Reinforcement Learning

Research on Path Planning of Mobile Robot Based on Reinforce...

引用

2022 Chinese automation Congress, CAC 2022

作者： Ji, Maoyuan Li, Jianxing Li, Shanqiang Liu, Zhenyu Song, Jiang Liu, Lisang Fujian Institute of Engineering Fujian Industrial Automation Technology Research and Development Center Fuzhou China Fujian Institute of Engineering Department of Computer Science and Mathematics Fuzhou China

ISBN: (纸本)9781665465335

With the continuous change of artificial intelligence technology, the study of path planning for mobile robots is no longer limited to traditional path algorithms. Reinforcement learning, as an artificial intelligence algorithm with excellent performance in the field of path planning, has also gradually become the object of research on path planning. In order to find a fast path from the starting point to the end point of a mobile robot in a complex environment, reinforcement learning is used to find a valid path by sensing the environment and continuously receiving rewarding feedback through a method of trial and error learning like humans. Therefore, this paper selects two algorithms to verify their effectiveness on the basis of building a two-dimensional grid map. The final experimental results show that both reinforcement learning algorithms can eventually avoid obstacles and plan a valid path in a complex environment through continuous learning iterations. Q-Learning also reduces the path distance by 10% and the number of convergence iterations by 82% compared to Sarsa. © 2022 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Tomo-NeRL: Tomographic neural representation learning for implicit CT image reconstruction

Tomo-NeRL: Tomographic neural representation learning for im...

引用

2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Tang, Xiaoqin Tan, Boheng Guo, Yuanhao Yu, Xianping Kendrick, Jake Reynolds, Mark Southwest University College of Computer and Information Science Chongqing China Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan China Research Institute of Highway Ministry of Transport Beijing China The University of Western Australia School of Physics Mathematics and Computing Perth Australia Perth Australia

ISBN: (纸本)9798350386226

CT image reconstruction is a challenging inverse problem of estimating image intensities from sensor signals. While deep learning-based methods hold promise, they are typically classified into fully-supervised, self-supervised, and case-by-case approaches, each offering distinct advantages and limitations. Among these, case-by-case reconstruction techniques, exemplified by models like NeRP, provide the advantage of flexible data-sampling and image sizes, making them well-suited for the complex CT inverse problem. However, existing case-by-case models encounter difficulties in achieving precise reconstructions, particularly in sparse-view scenarios. To address this limitation, we propose tomo-NeRL, a novel implicit reconstruction model that incorporates tomographic information of individual pixels within the reconstruction network. By harnessing this tomo-graphic data for implicit inverse learning, tomo-NeRL enhances reconstruction quality while effectively mitigating artifacts. The core innovation of tomo-NeRL lies in defining and extracting tomographic insights, such as visual characteristics and spatial variations specific to tomographic imaging, from the sinogram data for individual pixels. Moreover, our work introduces an adaptive inversion framework that amalgamates tomographic information from diverse projection angles, constructing a latent feature space that enhances the reconstruction process. Extensive experiments unequivocally showcase tomo-NeRL's outstanding reconstruction performance, excelling in artifact suppression and detail preservation, especially in sparse-view scenarios. © 2024 IEEE.

关键词： Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

Robustness Investigation of FOC of PMSG Based Variable-Speed Wind Turbine Connected on Grid

Robustness Investigation of FOC of PMSG Based Variable-Speed...

引用

International Conference on Advanced Electrical Engineering (ICAEE)

作者： Mohammed AOUMRI Abdelkader HARROUZ Ibrahim YAICHI Seddik BAALA Patrice WIRA Laboratoire de Développement Durable et Informatique (LDDI) University of Ahmed Draïa Adrar Algeria Institute for Research in Computer Science Mathematics Automation and Signal University of Haute Alsace Mulhouse France

ISBN: (数字)9798350349351

ISBN: (纸本)9798350349368

关键词： Wind energy generation Systematics Wind speed Robustness Synchronous generators Permanent magnets Stability analysis Wind turbines Security Wind energy conversion

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：