检索结果-内蒙古大学图书馆

Automation 5.0: The Key to Systems Intelligence and Industry 5.0

IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1723-1727页

作者： Ljubo Vlacic Hailong Huang Mariagrazia Dotoli Yutong Wang Petros A.Ioannou Lili Fan Xingxia Wang Raffaele Carli Chen Lv Lingxi Li Xiaoxiang Na Qing-Long Han Fei-Yue Wang Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith UniversityNathanQLD 4111Australia Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic UniversityHong KongChina Department of Electrical and Information Engineering Polytechnic of Bari70126 BariItaly State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190and also with the Qingdao Academy of Intelligent IndustriesQingdao 266114China Department of Electrical Engineering-Systems University of Southern CaliforniaLos AngelesCA 90007 USA School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 Beijing Huairou Academy of Parallel Sensing Beijing 101499China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University IndianapolisIndianapolisIN 46202 USA Department of Engineering University of CambridgeCB21TN CambridgeU.K. School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Dazhou Artificial Intelligence Institute Dazhouand the Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

AUTOMATION has come a long way since the early days of mechanization,i.e.,the process of working exclusively by hand or using animals to work with *** rise of steam engines and water wheels represented the first generation of industry,which is now called Industry Citation:***,***,***,***,***,***,***,***,***,***,***,Q.-***,and F.-***,“Automation 5.0:The key to systems intelligence and Industry 5.0,”IEEE/CAA ***,vol.11,no.8,pp.1723-1727,Aug.2024.

关键词： Automation machinery intelligence

来源：评论

学校读者我要写书评

暂无评论

Sentiment Summarization Generation Based on Multi Instance Learning and Graph Convolution on Social Media

Sentiment Summarization Generation Based on Multi Instance L...

引用

International Conference on computer Supported Cooperative Work in Design

作者： Bingshu Shi Meiling Liu Jiyun Zhou Kaiqun Fu School of Computer and Control Engineering Northeast Forestry University Harbin China Lieber Institute Johns Hopkins University Baltimore USA Department of Electrical Engineering and Computer Science South Dakota State University Brookings USA

ISBN: (数字)9798350349184

ISBN: (纸本)9798350349191

Sentiment summary generation task is very valuable in social media, which can extract different aspects from people’s evaluation of products or services, such as the quality of products, and generate summarized opinionated sentiment summaries. And nowadays, sentiment summarization still suffers from insufficient contextual information capture and incorrect and comprehensive aspect extraction. In this paper, we propose a new strategy to solve the above problems: firstly, MILNET is used to automatically identify aspects related to a product or service from a large number of user reviews, and then the results are inputted into GCN, which is used to enhance the importance of contextual words close to the aspect; meanwhile, E-MABA is utilized for further optimization of the model on aspect extraction. By conducting a large number of experiments on the OPOSUM dataset and comparing the existing state-of-the-art methods, it is found that our method achieves better performance than other methods, proving the feasibility and effectiveness of our proposed strategy.

关键词： Analytical models Vocabulary Sentiment analysis Social networking (online) Reviews Predictive models Data mining

来源：评论

学校读者我要写书评

暂无评论

ECG Signal Anomaly Detection Algorithm Based on CNN-BiLSTM 11

ECG Signal Anomaly Detection Algorithm Based on CNN-BiLSTM

引用

11th International Conference of Information and Communication Technology, ICTech 2022

作者： Cui, Kai Xing Xia, Xiao Jun School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing100049 China Shenyang Institute of Computing Technology Chinese Academy of Sciences Liaoning Shenyang110168 China

ISBN: (数字)9781665496940

ISBN: (纸本)9781665496940

Aiming at the problems of low feature extraction efficiency and low detection accuracy of traditional ECG signal detection algorithms, this paper proposes a convolutional neural network (CNN) and bi-directional long short-term memory (Bi-directional long short-term memory, LSTM) network hybrid ECG signal anomaly detection algorithm. This model effectively utilizes the ability of CNN to automatically extract features and BiLSTM's ability to efficiently process time series data. Through experimental verification on the arrhythmia data set in the MIT-BIH database, the overall accuracy of the model is 98.56%. Compared with support vector machine (SVM) and bidirectional long short-term memory neural network (BiLSTM), the accuracy and F1 value of this model are improved. © 2022 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Direct data-driven state-feedback control of general nonlinear systems

arXiv

引用

arXiv 2023年

作者： Verhoek, Chris Koelewijn, Patrick J.W. Haesaert, Sofie Tóth, Roland The Dept. of Electrical Engineering The Eindhoven University of Technology Netherlands The Institute for Computer Science and Control Budapest Hungary

Through the use of the Fundamental Lemma for linear systems, a direct data-driven state-feedback control synthesis method is presented for a rather general class of nonlinear (NL) systems. The core idea is to develop a data-driven representation of the so-called velocity-form, i.e., the time-difference dynamics, of the NL system, which is shown to admit a direct linear parameter-varying (LPV) representation. By applying the LPV extension of the Fundamental Lemma in this velocity domain, a state-feedback controller is directly synthesized to provide asymptotic stability and dissipativity of the velocity-form. By using realization theory, the synthesized controller is realized as a NL state-feedback law for the original unknown NL system with guarantees of universal shifted stability and dissipativity, i.e., stability and dissipativity w.r.t. any (forced) equilibrium point, of the closed-loop behavior. This is achieved by the use of a single sequence of data from the system and a predefined basis function set to span the scheduling map. The applicability of the results is demonstrated on a simulation example of an unbalanced disc. © 2023, CC BY-NC-SA.

关键词： Linear systems

来源：评论

学校读者我要写书评

暂无评论

Carbon-Aware Computing in a Network of Data Centers: A Hierarchical Game-Theoretic Approach

Carbon-Aware Computing in a Network of Data Centers: A Hiera...

引用

European control Conference (ECC)

作者： Enno Breukelman Sophie Hall Giuseppe Belgioioso Florian Dörfler Division of Decision and Control Systems KTH Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm Sweden Department of Electrical Engineering and Information Technology Automatic Control Laboratory ETH Zurich Zürich Switzerland

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Over the past decade, the continuous surge in cloud computing demand has intensified data center workloads, leading to significant carbon emissions and driving the need for improving their efficiency and sustainability. This paper focuses on the optimal allocation problem of batch compute loads with temporal and spatial flexibility across a global network of data centers. We propose a bilevel game-theoretic solution approach that captures the inherent hierarchical relationship between supervisory control objectives, such as carbon reduction and peak shaving, and operational objectives, such as priority-aware scheduling. Numerical simulations with real carbon intensity data demonstrate that the proposed approach success-fully reduces carbon emissions while simultaneously ensuring operational reliability and priority-aware scheduling.

关键词： Data centers Processor scheduling Computational modeling Carbon dioxide Games Supervisory control Resource management

来源：评论

学校读者我要写书评

暂无评论

Few-shot Object Detection Algorithm Based on YOLOv8-Mamba-Like Linear Attention 16

Few-shot Object Detection Algorithm Based on YOLOv8-Mamba-Li...

引用

16th International Conference on Communication Software and Networks, ICCSN 2024

作者： Wang, Hongliang Wang, Kaizhu Ji, Binglong Deng, Changyi Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Liaoning Province Human- Computer Interaction System Engineering Research Center Based on DigitTwin Shenyang China Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Shenyang China Institute of Software China Industrial Control Systems Cyber Emergency Response Team Beijing China

ISBN: (纸本)9798331506322

In the production and assembly process, the accuracy of detection is usually low due to limited resources and small quantities. In this paper, we propose a few-shot learning method for object detection based on the combination of YOLOv8 and Mamba-Like Linear Attention (MLLA) module. This method utilizes a high-pixel camera to capture the shape and size of the workpiece. By consistency-based mutual augmentation structure for few-shot samples data augmentation. By introducing the efficient and lightweight MLLA module, the model's speed and accuracy in object detection and segmentation tasks on mobile devices are significantly improved. Specifically, MLLA mainly integrates the two key elements of 'forget gate' and 'block design' in Mamba, and MLLA replaces forget gate by using position coding (RoPE) to provide necessary location information while maintaining parallel computation and fast inference speed. This makes MLLA improves the accuracy of detection and segmentation recognition. Experimental results show that compared to the original YOLOv8 model, the model with the MLLA module exhibits improvements in segmentation precision and recognition accuracy. This method demonstrates high accuracy and robustness in workpiece recognition, making it suitable for real-time industrial applications. © 2024 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Optimal Configuration of Self-Consistent Microgrid System with Hydrogen Energy Storage for Highway Service Area

引用

IFAC-PapersOnLine 2023年第2期56卷 7960-7965页

作者： Ruifeng Shi Keyi Tang Kwang Y. Lee School of Control and Computer Engineering North China Electric Power University Beijing China China Institute of Energy and Transportation Integrated Development Beijing 102206 China Department of Electrical and Computer Engineering Baylor University TX 76798 USA

Targeting on the goal of carbon peaking and carbon neutralization, the transportation sector is facing the pressure of carbon reduction, emission reduction and energy transformation simultaneously. Building a green, flexible, self-consistent and sustainable road transportation energy integration system has become an inevitable trend for the future development in an area without power grid. This paper proposes a self-consistent micro grid system model for wind and solar power with hydrogen energy storage for a highway service area without power grid connection. On this basis, a micro grid optimal configuration model is proposed with the goal of minimizing the comprehensive cost of the micro grid in the service area, under the constraints of the battery, hydrogen energy storage system (ESS), and the power balance of the micro grid system. Particle Swarm Optimization (PSO) algorithm is employed to solve the problem for a case study to verify the effectiveness of the model and the method proposed. Experimental results show that the model proposed in this paper not only improves the renewable energy utilization rate of the system, but also improves the reliability of power supply, verifying the effectiveness of the micro grid configuration scheme for the highway service area containing hydrogen ESS.

关键词： Self-consistent transportation energy system Self-consistent micro grid system Hydrogen energy storage system Optimal microgrid configuration

来源：评论

学校读者我要写书评

暂无评论

A Distributed Time-Varying Optimization Algorithm For Networked Lagrangian Agents Generating Continuous control Torques

A Distributed Time-Varying Optimization Algorithm For Networ...

引用

American control Conference (ACC)

作者： Yong Ding Hanlei Wang Jie Mei Wei Ren Department of Electrical and Computer Engineering University of California Riverside CA USA Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control Engineering Beijing China School of Mechanical Engineering Harbin Institute of Technology Shenzhen China

In this paper, the distributed time-varying optimization problem is investigated for networked Lagrangian systems with parametric uncertainties. Due to the usage of the signum function in the control torque design, there might exist chattering while implementing the distributed time-varying optimization algorithms for networked Lagrangian agents in the existing works. To this end, we design a distributed optimization algorithm that is capable of generating continuous control torques and achieving exact optimum tracking. A simulation is presented to validate the effectiveness of the proposed algorithm.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Differentially Private Online Federated Learning with Correlated Noise

Differentially Private Online Federated Learning with Correl...

引用

IEEE Conference on Decision and control

作者： Jiaojiao Zhang Linglingzhi Zhu Mikael Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Systems Engineering and Engineering Management Chinese University of Hong Kong

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

We introduce a novel differentially private algorithm for online federated learning that employs temporally correlated noise to enhance utility while ensuring privacy of continuously released models. To address challenges posed by DP noise and local updates with streaming non-iid data, we develop a perturbed iterate analysis to control the impact of the DP noise on the utility. Moreover, we demonstrate how the drift errors from local updates can be effectively managed under a quasi-strong convexity condition. Subject to an $(\epsilon, \delta)$ DP budget, we establish a dynamic regret bound over the entire time horizon, quantifying the impact of key parameters and the intensity of changes in dynamic environments. Numerical experiments confirm the efficacy of the proposed algorithm.

关键词： Privacy Federated learning Heuristic algorithms Noise Signal processing algorithms Servers

来源：评论

学校读者我要写书评

暂无评论

Configuration Optimization of Hybrid Electrolyzer for Wind-Based Green Hydrogen Production System

Configuration Optimization of Hybrid Electrolyzer for Wind-B...

引用

China International Electrical and Energy Conference (CIEEC)

作者： Jiahu Lin Wenbo Hao Mingfei Ban Northeast Forestry University College of Computer and Control Engineering Harbin China State Grid Heilongjiang Electric Power Research Institute Harbin China

ISBN: (数字)9798350359558

ISBN: (纸本)9798350359565

As the development of renewable energy progresses, the prospects for the application of green hydrogen are gradually expanding, with countries strengthening the construction of industries related to green hydrogen. This paper investigates the hybrid electrolytic hydrogen production system and its configuration optimization problem, considering wind power decomposition and multiple types of electrolyzers. Firstly, a model for wind power redistribution is established based on the characteristics of different types of electrolyzers to determine the power loads of each type. Subsequently, based on the solution results of the redistribution model, a hybrid electrolyzer system configuration optimization model with the objective of maximizing annual revenue is proposed. Finally, case studies show that Hybrid electrolyzer system offers advantages in terms of energy efficiency, reliability and economy. Compared to alkaline electrolyzer system, hybrid system can improve the efficiency and stability of energy utilization and better cope with the uncertainty of renewable energy sources. The hybrid system can significantly reduce the initial capital investment and number of configurations compared to proton exchange membrane electrolyzer system, thereby lowering the operating cost of the overall energy system.

关键词： Production systems Costs Uncertainty Wind energy Wind speed Wind power generation Green hydrogen

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：