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检索条件"机构=Dept. of Automation and Computer Engineering"

共 700 条记录，以下是161-170 订阅

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Intelligent Control Algorithm for Power Balance Between Microgrids

Intelligent Control Algorithm for Power Balance Between Micr...

引用

On-Line Conference (ONCON), Industrial Electronics Society Annual

作者： David Carrasco-González Raúl Sarrias-Mena Pablo Horrillo-Quintero Francisco Llorens Iborra Luis M. Fernández-Ramírez Department of Electrical Engineering SURET Research Group University of Cadiz (UCA) ETSI Algeciras Spain Dept. of Engineering in Automation Electronics and Computer Arch. and Networks SURET Reseach Group UCA ETSI Algeciras Spain

Microgrid clusters are becoming increasingly popular owing to their many benefits and their ability to meet human needs in terms of energy flexibility, security, and integration of renewable sources. They are composed of interconnected microgrids with a variety of power generation sources, loads, and storage devices. Microgrid clusters can also combine DC and AC technologies, even within a single microgrid. In this work, a new energy management system is developed for a microgrid cluster consisting of two microgrids connected to the main grid. The proposed energy management system, acting as the centralized control layer in the microgrid cluster, is based on a fuzzy-logic algorithm. The microgrid cluster consists of an AC microgrid integrating a photovoltaic generator, a battery bank and AC loads; and a DC microgrid composed of a wind turbine, electrolyzer, ultracapacitor, fuel cell and DC loads. The microgrid cluster is tested under different working conditions, such as variable wind speed and solar irradiance, and connection and disconnection of the loads. Finally, the energy management system implemented in the microgrid cluster exhibits a correct behaviour under different conditions, according to the results obtained.

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A CNN-LSTM based approach for image captioning

A CNN-LSTM based approach for image captioning

引用

7th IET Smart Cities Symposium (SCS 2023)

作者： Esra Balık Mehmet Kaya Buket Kaya Department of Sofware Engineering Bandırma Onyedi Eylül University Balıkesir Turkey Department of Computer Engineering Fırat University Elazığ Turkey Dept. of Electronics and Automation Fırat University Elazığ Turkey

In this age of information and visual data, it has become necessary in many fields to draw meaningful conclusions from these visual data and express them in a textual context. A visual data makes it more understandable and valuable with a textual explanation. It will also greatly accelerate the scanning of large amounts of data in many application areas. In basic fields such as education or medicine, visual-text pairs are of great importance to use as materials. In addition, many autonomous vehicles can be designed that enable disabled individuals to use visual and textual information together. Such studies have gained a wider application area, especially with the advancement of deep learning technology. In this study, a study was carried out on the Flickr8k dataset using Convolutional Neural Networks (CNN) and Long Short Term Memory (LSTM) technologies to title visual data. This model provides an integrated structure for understanding visual data and producing textual descriptions. The accuracy of the caption value created with the BLEU-1 metric was evaluated. In addition, other studies carried out together with this study were discussed and information was given about the performance of these methods.

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Orientation Invariant Tensor Completion In Both Spectual And Space Domains

Orientation Invariant Tensor Completion In Both Spectual And...

引用

2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)

作者： Xiangrui Li Andong Wang Xiyuan Hu Zhenmin Tang Dept. Computer Technology and Engineering Nanjing University of Science and Technology Nanjing China The School of Automation Guangdong University of Technology Guangzhou China

The performance of most tensor completion algorithms heavily relies on the definition of tensor low-rankness. Among the various low-rank regularizations proposed in the last decade, the Tubal+Tucker Nuclear Norm (T2NN) firstly considers the low rankness both in spectral and space domains. However, this norm is unfortunately sensitive to the orientation, and thus fails to model low-rankness in multiple orientations. To this point, a new tensor norm, dubbed Orientation Invariant Hybrid Nuclear Norm (OIHNN), is first defined and then applied to formulate a new tensor completion model. To solve the model, an efficient algorithm is developed within the framework of Alternating Direction Method of Multipliers (ADMM). Effectiveness of our method is validated through experimental results on real datasets.

关键词： Tensors Containers Convex functions Intelligent agents

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Surrogate-Assisted Multi-Class Collaborative Teaching and Learning Optimizer for High-Dimensional Industrial Optimization Problems

Surrogate-Assisted Multi-Class Collaborative Teaching and Le...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Jing Bi Ziqi Wang Haitao Yuan Jinhong Yang Jia Zhang College of Computer Beijing University of Technology Beijing China Beijing Laboratory of Smart Environmental Protection Beijing University of Technology Beijing China School of Automation Science and Electrical Engineering Beihang University Beijing China CSSC Systems Engineering Research Institute Beijing China Dept. of Computer Science Lyle School of Engineering Southern Methodist University Dallas TX USA

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Swarm intelligence and evolutionary algorithms are widely applied in industrial scheduling, mobile edge computing, etc due to their strong robustness and fast optimization speed. However, some real-world industrial optimization problems involve numerous decision variables, known as high-dimensional problems. Current algorithms often require considerable computational resources to evaluate objective function values because of high-dimensional decision spaces. Moreover, they are also prone to be trapped in local optima. To solve the above problems, this work proposes an improved algorithm named Surrogate-assisted Multi-class Collaborative Teaching and learning optimizer (SMCT). A multi-class collaborative teaching and learning optimizer is proposed as a base optimizer to improve exploration and exploitation abilities. Furthermore, an autoencoder-assisted radial basis function is proposed as the surrogate model to replace true function evaluations, thereby saving computational resources and balancing the complexity and accuracy in fitting true models. Finally, experimental results demonstrate that SMCT surpasses its existing peers in both search accuracy and convergence speed across eight high-dimensional benchmark functions.

关键词： Accuracy Processor scheduling Computational modeling Education Autoencoders Collaboration Search problems Space exploration Particle swarm optimization Optimization

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Assessment of Slime Mould Algorithm Based Real PID Plus Second-order Derivative Controller for Magnetic Levitation System 5

Assessment of Slime Mould Algorithm Based Real PID Plus Seco...

引用

5h International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2021

作者： Izci, Davut Ekinci, Serdar Eker, Erdal Dundar, Ahmet Batman University Dept. of Electronics and Automation Batman Turkey Batman University Department of Computer Engineering Batman Turkey Muş Alparslan University Vocational School of Social Sciences Muş Turkey

ISBN: (纸本)9781665449304

This paper aims to demonstrate the success of a recently developed metaheuristic algorithm, named slime mould algorithm (SMA), for efficient operation of a magnetic levitation system. A real proportional-integral-derivative (PID) plus second-order derivative (PIDD2) controller was utilized to demonstrate the implementation. This paper is also the first report on SMA based real PIDD2 controller tuning for control of a magnetic levitation system. The transient response analysis was performed to demonstrate the promise of the proposed approach. Besides, a comparative performance analysis in terms of transient stability was also performed by using other available and good performing approaches. The results have shown the SMA based real PIDD2 controller to be a better choice for efficient operation of a magnetic levitation system. © 2021 IEEE.

关键词： Controllers

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Improving Arithmetic Optimization Algorithm Through Modified Opposition-based Learning Mechanism 5

Improving Arithmetic Optimization Algorithm Through Modified...

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5h International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2021

ISBN: (纸本)9781665449304

This study aims to present a novel hybrid metaheuristic algorithm through improving the performance of the arithmetic optimization algorithm (AOA). A modified version of opposition-based learning mechanism (mOBL) has been used to provide the improvement. The greater performance of the improved version of the arithmetic optimization algorithm (mOBL-AOA) has been demonstrated through statistical and non-parametric tests by using benchmark functions of Schwefel 2.22, Rosenbrock, Step, Schwefel, Ackley and Penalized. The results were demonstrated comparatively by using sine cosine, Lévy flight distribution and the original arithmetic optimization algorithms. The performed comparative analyses have confirmed the highly competitive performance of the mOBL-AOA algorithm in terms of tackling with the the optimization problems. © 2021 IEEE.

关键词： Benchmarking

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The Neural Network for Vertical Handover Procedure

The Neural Network for Vertical Handover Procedure

引用

2020 IEEE International Conference on Problems of Infocommunications Science and Technology, PIC S and T 2020

作者： Semenova, Olena Semenov, Andriy Voitsekhovska, Olha Kozin, Dmytro Vinnytsia National Technical University Dept. of Telecommunication Systems and Television Vinnytsia Ukraine Vinnytsia National Technical University Dept. of Radio-Frequency Engineering Vinnytsia Ukraine Vinnytsia National Technical University Faculty for Computer Systems and Automation Vinnytsia Ukraine

ISBN: (纸本)9781728191775

The paper suggests to apply a neural network in cellular networks in order to improve the vertical handover process. The proposed neural network is a multilayer perceptron. The paper presents the proposed architecture of the neural network. The operation of the perceptron has been described. Simulation of the neural network operation in Matlab software was performed. © 2020 IEEE.

关键词： MATLAB

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Active Disturbance Rejection Control for 3D Crane Systems 11

Active Disturbance Rejection Control for 3D Crane Systems

引用

11th International Conference on Information Technology and Quantitative Management, ITQM 2024

作者： Roman, Raul-Cristian Precup, Radu-Emil Petriu, Emil M. Politehnica University of Timisoara Dept. Automation and Applied Informatics Bd. V. Parvan 2 Timisoara300223 Romania Center for Fundamental and Advanced Tech. Res. Romanian Academy - Timisoara Br. Bd. Mihai Viteazu 24 Timisoara300223 Romania University of Ottawa School of Electrical Engineering and Computer Science 800 King Eduard OttawaONK1N 6N5 Canada

Active Disturbance Rejection Control (ADRC) is a data-driven algorithm that offers a promising approach for robust control design. This paper investigates the effectiveness of first-order and second-order ADRC for 3D cranes. To compare the results fairly and reduce the heuristics in parameter tuning, the ADRC parameters were optimally computed via the African Vultures Optimization Algorithm. Both controllers based on ADRC are validated using experiments on a 3D crane laboratory system and their design and performance evaluation are done by minimizing the sum of squared errors. The results demonstrate the robustness of the ADRCs. This comparative analysis highlights the advantages and limitations of both control strategies, providing valuable insights for selecting the appropriate ADRC order for specific applications. © 2024 The Authors.

关键词： Disturbance rejection

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Live Demo: E2P-Events to Polarization Reconstruction from PDAVIS Events

Live Demo: E2P-Events to Polarization Reconstruction from PD...

引用

2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Delbruck, Tobi Wang, Zuowen Mei, Haiyang Haessig, Germain Joubert, Damien Haque, Justin Chen, Yingkai Milde, Moritz B. Gruev, Viktor Univ. of Zurich and ETH Zurich Sensors Group Institute of Neuroinformatics Switzerland Center for Vision Automation & Control High-Performance Vision Systems AIT Austrian Institute of Technology Vienna Austria Western Sydney University Intl. Centre for Neuromorphic Systems The MARCS Institute Sydney Australia University of Illinois at Urbana-Champaign Dept. of Electrical and Computer Engineering UrbanaIL United States

This demonstration shows live operation of of PDAVIS polarization event camera reconstruction by the E2P DNN reported in the main CVPR conference paper Deep Polarization Reconstruction with PDAVIS Events (paper 9149 [... 详细信息

ISBN: (纸本)9798350302493

关键词： Polarization

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Behavioural Cloning for Serious Games in Support of Pediatric Neurorehabilitation

Behavioural Cloning for Serious Games in Support of Pediatri...

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Mediterranean Conference on Control and automation (MED)

作者： Federico Baldisseri Edoardo Montecchiani Arturo Maiani Danilo Menegatti Alessandro Giuseppi Antonio Pietrabissa Vincenzo Fogliati Francesco Delli Priscoli Dept. of Computer Control and Management Engineering (DIAG) Sapienza University of Rome Italy 4You – Association for Social Advancement Rome Italy Consortium for the Research in Automation and Telecommunication (CRAT) Rome Italy

Behavioural Cloning is a Machine Learning method concerning how a machine attempts to autonomously mimic the actions of a human, or in general a complex controller, performing a given task. This work innovatively exploits Behavioural Cloning in support of Pediatric Neurorehabilitation. In particular, an Artificial Neural Network Classifier has been implemented to autonomously adapt the difficulty, through a set of tunable parameters, of a Serious Game that was specifically developed to stimulate some relevant cognitive capabilities of the patient. Data augmentation via Behavioural Cloning allows such autonomous difficulty adaptation system to improve its classification performances and, thus, to enforce a control logic that, in turn, improves the effectiveness of the cognitive training. The system is validated through an experimental assessment on a Serious Game that trains motor coordination: experimental results of children gameplay are analyzed and discussed.

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