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检索条件"任意字段=International Conference on Electrical Engineering Computing Science and Automatic Control"

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Adaptive AGC Strategy with Online Equivalent Model Parameter Identification 4

Adaptive AGC Strategy with Online Equivalent Model Parameter...

引用

4th IEEE international conference on Electronic Technology, Communication and Information, ICETCI 2024

作者： Ma, Ruicong Cao, Yongji Zhang, Yi Zhang, Hengxu Li, Baoliang Zou, Shihao Shandong University School of Electrical Engineering Jinan China Shandong University Academy of Intelligent Innovation Jinan China State Grid Jinan Power Supply Company Jinan China

ISBN: (纸本)9798350361643

The uncertainty of wind and photovoltaic energy brings challenges to the system frequency regulation. Thus, this paper proposes an adaptive control strategy for automatic generation control (AGC) considering the grid structure change. Firstly, online identification method of grid structure and parameters is carried out to obtain the regional frequency control model based on the online measurement data and the particle swarm optimization (PSO) algorithm is used to identify the grid structure parameters to obtain the regional frequency control model parameters. Then based on the area control error (ACE) criterion, the AGC parameters are solved by using the adaptive continuous tabu search according to the obtained regional frequency control model. The case study results show that the algorithm proposed in this paper can effectively improve the performance of AGCs. © 2024 IEEE.

关键词： Tabu search

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OLFV: Harnessing the Power of Enhanced Deep Learning Model to Recognize Fingerprints using Optimization and Classification Principles Paper

OLFV: Harnessing the Power of Enhanced Deep Learning Model t...

引用

2024 international conference on Advances in Data engineering and Intelligent computing Systems, ADICS 2024

作者： Natarajan, Senthil Kumar Rathinasabapathy, Ramadevi Gopal, Baskar Subramani, Karthikeyan Ramaswamy, Arikrishnaperumal Aravind Sathyabama Institute Of Science And Technology Department Of Electronics And Communication Engineering Chennai India Saveetha School Of Engineering Simats Department Of Biomedical Engineering Chennai India University Of Technology And Applied Sciences Department Of Electrical And Electronics Engineering College Of Engineering And Technology Nizwa Oman Rover Engineering College Elambalur Department Of Electronics And Communication Engineering Perambalur India Prince Shri Venkateshwara Padmavathy Engineering College Department Of Electronics And Communication Engineering Chennai India

ISBN: (纸本)9798350364828

Among many forms of biometric identification, fingerprints are among the most common. Due to their individuality, they are thought to be vital in forensics. Human operators have long been responsible for person identification. On the other hand, automatic fingerprint identification systems have emerged thanks to technology advancements, and their robustness is becoming more important as the population grows. The field of computer vision, however, has benefited greatly from deep learnings advancements. Optimized Learning for Fingerprint Verification (OLFV) is a new method for accurate fingerprint identification that is introduced in this paper. To test its efficacy, it is cross-validated with a traditional deep learning model, Convolutional Neural Network (CNN). While fingerprint analysis falls under the purview of computer vision and image processing, deep learning has seen relatively little use in this field thus far. Two steps in the automated fingerprint identification pipeline-fingerprint categorization and fingerprint minutiae extraction-are the subject of this study use of deep learning techniques. For those two phases, we build and evaluate deep learning systems according to several criteria, including dataset size and network design. A system that uses proposed convolutional models for decision making uses the preprocessed fingerprint photos. With the Optimized Learning for Fingerprint Verification variation reaching over 98.54% accuracy and the CNN variant reaching over 95.26%, the system is robust. The resulting section shows the proper proof to it in clear manner with graphical illustrations. © 2024 IEEE.

关键词： Learning systems

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Associative Memory Design Based on Region Attracivity Neural Networks and Reinforcement Learning

Associative Memory Design Based on Region Attracivity Neural...

引用

2023 international conference on Neuromorphic computing, ICNC 2023

作者： Bao, Gang Song, Zhenyan Zhou, Ranran China Three Gorges University Hubei Key Laboratory of Cascaded Hydropower Stations Operation & Control Electrical Engineering & New Energy Yichang443002 China

ISBN: (纸本)9798350316889

This paper introduces a novel associative memory design method based on neural networks which are region attractivity. For the given memory patterns, we can take any value for networks connection weights and then compute network external inputs based on reinforcement learning algoritms. One numerical experiment is given for validify our method. © 2023 IEEE.

关键词： Reinforcement learning

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Automation of Short Answer Grading Techniques: Comparative Study using Deep Learning Techniques 5

Automation of Short Answer Grading Techniques: Comparative S...

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5th IEEE international conference on electrical, Computer and Communication Technologies, ICECCT 2023

作者： Divya, Arunima Haridas, Vivek Narayanan, Jayasree Amrita School of Computing Deportment of Computer Science and Engineering Amritapuri India

ISBN: (纸本)9781665493604

automatic short answer grading (ASAG) techniques have been shown to cut down on the time and work needed to grade exams, and it is a method that is becoming more and more common, especially with the rise in popularity of online courses. This study compares the results of 7 pre-trained embedding models using just one feature to automatically grade brief responses: the similarity between the model answer's and the student answer's embeddings. Regression models are developed and evaluated to predict a short answer's score based on the similarities between all pairs of answers in the Mohler dataset. The predictions are evaluated by comparing the Root Mean Squared Error (RMSE) and Pearson correlation scores of each model. © 2023 IEEE.

关键词： Grading

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Iterative Learning Data Driven Strategy for Aircraft control System 9

Iterative Learning Data Driven Strategy for Aircraft Control...

引用

9th IEEE international conference on Cloud computing and Intelligence Systems, CCIS 2023

作者： Guo, Xiaoyong Wang, Jianhong Gao, Jia Henan University of Engineering College of Software Zhengzhou451191 China Jiangxi University of Science and Technology College of Electrical Engineering and Automation Ganzhou China

ISBN: (纸本)9798350304428

The paper extends our previous contributions about data driven control from the theory and practice in aircraft control system respectively, while achieving the combination of theory and practice. After feeding back the output signal to the input part, and get one error signal, three kinds of data are measured to design the unknown controller without any information about the unknown plant. Based on the internal essence of data driven control, iterative learning idea is introduced with data driven control to iterative leaning data driven control strategy. To get the optimal data driven controller, other knowledge are applied, for example, adaptation, optimization and learning. After reviewing the aircraft control system, our numerical simulation results have demonstrated the efficiency of this proposed iterative learning data driven control strategy. Finally, to achieve the combination with theory and practice, our proposed iterative learning data driven control is applied into aircraft control system, so that the considered aircraft can fly more remotely. © 2023 IEEE.

关键词： Aircraft control

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Irrigation control System for Seedlings Based on the Internet of Things 1

引用

international conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2022

作者： de Carvalho, André Kusuma, Gede Putra Handoyo, Alif Tri Department of Computer Science BINUS Graduate Program—Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

The agricultural activities in the Vocational School of Agricultural engineering (ESTVA) in Timor-Leste requires large quantities of water with high availability for the production and cultivation of plants. However, the crop results sometimes decrease due to challenges problem faced by the management of the water resources. This study aims to design an Internet of Things (IoT) based automatic control system to control water supply and maintain soil moisture conditions effectively. The evaluation of manual and automatic irrigation systems during the 21 days trial shows that the automatic system provides stable utilization of water with watering frequency of 274 occurs only in 12 days, with an amount of total watering of 35.3 L. Meanwhile, the manual system uses up to 49.8 L of water, which is 14.5 L more than the water spent by the automatic system. The results of the evaluation also indicate that automatic system obtains the average moisture value of 509 with a standard deviation of 63, which is smaller than the manual system that obtains an average moisture value of 559 and a significant standard deviation of 126. From these results, the automatic system is more effective in maintaining the soil moisture level and yet requires less water compared to the manual watering system. Furthermore, the quality and productivity of the growth of mustard seedlings with automatic system prove that the seeds are more stable and feasible to continue transplanting since the automatic system produces 12 more mustard trees compared to the manual system. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Soil moisture

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Smart Healthcare: A Logical Development of Medical Image Processing Based Sleep Apnea Disease Detection Using Elevated Neural Classification Principle

Smart Healthcare: A Logical Development of Medical Image Pro...

引用

2024 international conference on Innovative computing, Intelligent Communication and Smart electrical Systems, ICSES 2024

作者： Jagadeesh, P. Radhamani, V. Ravi, T. Charulatha, G. Shahare, D.Y. Aljawawdeh, Hamzeh J. Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering college Department of Electronics and Communication Engineering Avadi Chennai India Rajalakshmi Engineering College Department of Ece Chennai India Sathyabama Institute of Science and Technology Department of Ece Chennai India Selvam College of Technology Department of Biomedical Engineering Namakkal India Yeshwantrao Chavan College of Engineering Department of Mechanical Engineering Nagpur India Zarqa University Faculty of information technology Department of Software Engineering Zarqa Jordan University of Business and Technology Jeddah21448 Saudi Arabia

ISBN: (纸本)9798331543617

Entirely common sleep disorder is the dangerous wakefulness (Apnea) of breathing during snoring. In this study, we explore the possibility of how medical image processing can be useful and accurate method for sleep disordered breathing detection. The new approach named as Sleep Apnea Analyzing Strategy (SAAS) is firstly tested with the help of existing method namely Image base Sleep Apnea Analyzer (ISAA) that use less number or data to be processed and hence running on portable device delivering results much faster than other available methods, both being cross-validated against each other. Sleep Apnea Image-based Detector using Ephysiology - A new Algorithm (SAAS) We rely on sophisticated image processing techniques to extract relevant characteristics from medical images (such as x-rays, CT scans or MRIs) which are indicative of patterns typically associated with sleep apnea. The proposed methodology includes image preprocessing to improve the quality of images, feature extraction for quantification and characterization of all relevant information during OSA trials in GUI interface through well-known classification algorithms to classify patients with at least 20 de-saturations without sleep apnea. Our research aims to help in the creation of automatic diagnostic methods that will lead to early detection and treatment for sleep apnea. Our objective with this work is to provide a fair evaluation of the proposed technique in terms of sensitivity, specificity and accuracy through using a large dataset. © 2024 IEEE.

关键词： Sleep research

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Case Study of Robot Arm Billiards

Case Study of Robot Arm Billiards

引用

2023 international automatic control conference, CACS 2023

作者： Li, Jen-Hsing Chao, Chan-Hong Yu, Lin-Tai Dai, Chun-Yan Zhang, Jiang-Li Kun Shan University Electrical Engineering Department Tainan Taiwan

ISBN: (纸本)9798350306354

This paper mainly studies the function of the robot arm to play pool. To perform this function, a special gripper must be designed, so we use 3D printing to design a gripper mechanism for playing pool, and design the drive and control circuits for the gripper. In addition, we also design a camera to be installed on the gripper to provide image recognition. This paper only discusses the case study of "one cushion"bank shot. Bank shot is a playing pool technique in which the player shoots the object ball into the cushion first, and let the object ball bounce into the pocket. This practical study is a mechatronic system of a robotic arm with special-purpose functions. © 2023 IEEE.

关键词： Grippers

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An Innovation Development of Reliable Routing System Based on Industrial Conveyor Weighting and Management System 2

An Innovation Development of Reliable Routing System Based o...

引用

2nd IEEE international conference on Distributed computing and electrical Circuits and Electronics, ICDCECE 2023

作者： Kanniga, Devi Kumari, Neeraj Department of Computer Science and Engineering Bangalore India Teerthanker Mahaveer University College of Computing Science & It Department of Computing Science & It Moradabad India

ISBN: (纸本)9798350347456

Reliable routing systems for industrial conveyor weighing are essential for ensuring accurate weight readings and efficient operation. Conveyor weighing systems are used in a variety of industrial contexts, including food production and packaging, chemical processing, and the manufacturing of heavy equipment. The reliability of these systems is critical for the successful operation of these industries. The primary components of a reliable routing system for industrial conveyor weighing are the conveyor belt, the load sensors, and the control system software. The conveyor belt is the most essential part of the system, as it carries the material being weighed. The load sensors measure the weight of the material as it moves along the conveyor belt and sends this information to the control system. The software then processes the weight data and sends commands to the conveyor belt, adjusting its speed and direction to ensure accurate weight readings. A reliable routing system should also include safety features to protect operators and equipment. Sensors should be placed near the conveyor belt to detect any potential hazards and notify the operator accordingly. The system should also feature emergency stop buttons to quickly shut down the conveyor belt in the event of an emergency. Additionally, the system should be equipped with alarms and other warning systems to alert operators of any potential issues. © 2023 IEEE.

关键词： Chemical industry

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Study on Trajectory Planning and Error Analysis of automatic Spraying Robot on Steel Bridge Deck

Study on Trajectory Planning and Error Analysis of Automatic...

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2024 international conference on electrical and Computer engineering Researches, ICECER 2024

作者： Bo, Zhou Shu Da Yong, Tang Long, Ni Lin Feng, Xu Guo Chuan, Cao Chuan Yi, Yang Jun Hong, Hu Dai School of Intelligent Manufacturing Engineering Chongqing University of Arts and Sciences China Chongqing Lizhi Road and Bridge Engineering Co. LTD. Chongqing China Chongqing Pingshan Mechanical and Electrical Equipment Co. LTD. China

ISBN: (纸本)9798331539733

To address the issues of low efficiency and poor uniformity in manually applying a waterproof bonding layer on steel deck surfaces, we developed an automated spraying robot. We established a mathematical model based on the spraying mechanism and utilized Simulink for trajectory planning simulations. The results demonstrated the robot's ability to rapidly track the target trajectory with quick ***, we conducted operational simulations using the CoppeliaSim experimental platform to analyze the real-world performance of the spraying robot in a physics-based environment. Although some trajectory errors were observed during these simulations, they could be mitigated by optimizing the chassis parameters of the ***, through physical prototype testing, we analyzed the trajectory errors and optimized the control strategy by adjusting both the chassis parameters and the drive motor speeds. These adjustments brought the trajectory errors within an acceptable range. Prototype spraying tests confirmed the robot's capability to significantly enhance the efficiency and uniformity of the waterproof bonding layer application, indicating strong market potential. © 2024 IEEE.

关键词： Robot programming

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