检索结果-内蒙古大学图书馆

Dynamic Charging and Path Planning for UAV-Powered Rechargeable WSNs Using Multi-Agent Deep Reinforcement Learning

IEEE Transactions on Automation Science and engineering 2025年 22卷 15610-15626页

作者： Betalo, Mesfin Leranso Leng, Supeng Seid, Abegaz Mohammed Abishu, Hayla Nahom Erbad, Aiman Bai, Xiaoshan Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Hamad Bin Khalifa University Division of Information and Computing Technology College of Science and Engineering Doha Qatar Shenzhen University College of Mechatronics and Control Engineering National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China

Unmanned Aerial Vehicle (UAV)-powered 5G/6G networks integrated with rechargeable wireless sensor networks (RWSNs) offer promising solutions for extending system lifetime, collecting data, and providing computing services and power to sensor nodes (SNs). UAVs offer significant advantages, including exceptional mobility, cost-effective deployment, and the ability to be easily reprogrammed for a wide range of missions. However, the limited onboard power capacity of UAVs, coupled with the lack of dynamic and intelligent charging station (CS) management and inefficient path planning, can lead to SN failure in dynamic mobile environments. To address these challenges, we propose an energy-efficient laser-charged UAV (LCU)-enabled RWSN environment, wherein UAVs, powered by laser beams from ground-based stations, provide services, collect data, and transfer energy to SNs. We formulate a joint optimization problem involving power allocation, dynamic charging strategy (DCS), and path planning to minimize task completion time and sensor node death time. Given the NP-hard nature of the problem, we employ a stochastic game model based on a Markov decision process (MDP) for its solution. To solve this problem, we propose a deep reinforcement learning (DRL) based algorithm that enables real-time charging scheduling decisions while optimizing network performance. We introduce a multi-agent double deep Q-network (MA-DDQN) model to determine the optimal trajectories for all UAVs in large and complex environments. Simulation results demonstrate that the MA-DDQN approach outperforms state-of-the-art techniques, showing significant improvements in terms of average delay, energy consumption, and task completion time. © 2004-2012 IEEE.

关键词： Stochastic models

来源：评论

学校读者我要写书评

暂无评论

Intelligent Agricultural Drones Utilizing Nano-Fertilizer Dispensation for Precision Farming

Intelligent Agricultural Drones Utilizing Nano-Fertilizer Di...

引用

2024 International Conference on communication, Computing and Internet of Things, IC3IoT 2024

作者： Jayanthi, G. Nancy, W. Umamaheswari, B. Chithrakkannan, R. Sujith, R. Sathya Prasanna, S. Sri Sairam Engineering College Department Of Instrumentation And Control Engineering India Jeppiaar Institute Of Technology Department Of Electronics And Communication Engineering India Sri Sairam Engineering College Department Of Electronics And Communication Engineering India

ISBN: (纸本)9798350352689

An innovative approach to precision agriculture through the integration of artificial intelligence (AI) and nano-fertilizer technology in an agricultural drone system. The proposed system aims to optimize crop yield, reduce environmental impact, and enhance resource efficiency by employing advanced AI algorithms for crop health assessment and nano-fertilizers for targeted nutrient delivery. The drone's real-time decision-making capabilities, coupled with precise dispensation of nano-sized fertilizers, contribute to sustainable farming practices. Field trials demonstrate promising results in terms of improved crop productivity, resource utilization, and minimized environmental footprint. © 2024 IEEE.

关键词： Crops

来源：评论

学校读者我要写书评

暂无评论

A Method for Filtering Data-Driven Predictive control Aimed at Vehicle Lateral Stabilization in Compacted-Snow Rutted Road Conditions 8

A Method for Filtering Data-Driven Predictive Control Aimed ...

引用

8th CAA International Conference on Vehicular control and Intelligence, CVCI 2024

作者： Zhao, Xu Guo, Hongyan Shi, Wanqing College of Communication Engineering Jilin University Changchun China Jilin Institute of Chemical Technology Department of Aircraft Control and Information Engineering Changchun China College of Communication Engineering Jilin University State Key Laboratory of Automotive Simulation and Control Changchun China

ISBN: (纸本)9798331504892

Designing a data-driven predictive controller for lateral stability of vehicles on compacted-snow rutted roads, especially when the data is subjected to non-stationary noise disturbances, is a significant challenge. This paper introduces a novel subspace predictive equation construction method that incorporates filtering using the inverse of a first-order disturbance model. Based on this, a filtering data-driven predictive controller is designed. The proposed method is tested through numerical simulations and MATLAB/CarSim co-simulation. Simulation results show that the proposed subspace predictive equation with filtering effectively mitigates the variance and bias introduced by non-stationary noise. The co-simulation results demonstrate that the controller ensures the stability and robustness of the vehicle system. © 2024 IEEE.

关键词： Predictive control systems

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Machine Learning Models for Solar Power Prediction Using Time Series Weather Data 3

Comparative Analysis of Machine Learning Models for Solar Po...

引用

3rd IEEE International Conference on Power Electronics, Intelligent control and Energy Systems, ICPEICES 2024

作者： Kane, Sumedh Nilesh Rathore, Akshit Abhijeet Anees, Sanya Kane, Arati Electronics and Communication Engineering Netaji Subhas University of Technology Delhi India Instrumentation and Control Engineering Bharati Vidyapeeth College of Engineering Delhi India

ISBN: (纸本)9798350387193

Smart Grids preside over traditional power grids due to their efficiency and effectiveness. Smart grid implementation has benefited all components of the power system. These grids usually generate energy from renewable energy resources. However, the stability, reliability, and seamless functioning of the grid are adversely affected by the highly weather-dependent characteristics of renewable energy sources. As a result, accurate energy generation forecasting is an essential requirement for the grid's steady and reliable operation. The forecasting techniques for the quantity of electricity produced by solar power plants are discussed in this study. First, the impact of weather on solar power generation is investigated. Second, a machine learning method for solar panel output power prediction based on weather conditions is proposed. Finally, an ensemble approach utilizing different algorithms for machine learning is utilized to boost the accuracy of the proposed model. For the objective of creating prediction models, we utilized a variety of techniques, including temporal convolutional neural networks, fine trees, support vector machines with different kernel functions, artificial neural networks, and long-short-term memory RNNs. Each model's prediction accuracy has been assessed by comparing and contrasting these different methods. A comparative investigation indicated that the Temporal Convolutional Network-based model trumps the others in terms of efficiency. The proposed ensemble model exceeded the conventional individual models after performance comparison with the standard approaches. © 2024 IEEE.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

SIE: infrared and visible image fusion based on scene information embedding

引用

Multimedia Tools and Applications 2025年第3期84卷 1463-1488页

作者： Geng, Yingnan Diao, Weixuan Zhao, Yan Electrical and Information Engineering Changchun Institute of Technology Kuanping Road Jilin Changchun130103 China Information and Control Engineering Jilin Institute of Chemical Technology Chengde Street Jilin Jilin132022 China College of Communication Engineering Jilin University Qianjin Street Jilin Changchun130015 China

In this article, we proposed an infrared and visible image fusion method based on scene information embedding, which is to obtain an fused image with high-quality target information such as pedestrian crossing, vehicles, signs and rich background texture information. First, scene information is described, so as to effectively represent highlight salient target for infrared image and texture detail for visible image. Second, we embed this scene information into multi-scale fusion framework to fuse these information and reconstruct the desired fused image. It is worth noting that scene information is constructed by pre-trained convolutional neural network, where not only information extracted by convolutional neural network is fully utilized, but also training complexity is not increased. In datasets LLVIP, MSRS, M3FD,TNO, RoadScene and elctricity1, the superiority of our proposed algorithm SIE over state-of-the-arts is demonstrated by subjective evaluation and objective evaluation including information entropy (EN), standard deviation (SD), spatial frequency (SF), average gradient (AG), sum of the correlations of differences (SCD) and mutual Information (MI) metrics. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image fusion

来源：评论

学校读者我要写书评

暂无评论

Comparison of pulse rate variability from post-auricula and heart rate variability during different body states for healthy subjects

引用

Journal of Medical engineering and technology 2023年第3期47卷 179-188页

作者： Qi, Yusheng Zhang, Aihua Ma, Yurun Chang, Tingting Xu, Jianwen College of Electrical and Information Engineering Lanzhou University of Technology Lanzhou China Key Laboratory of Gansu Advanced Control for Industrial Processes Lanzhou University of Technology Lanzhou China National Demonstration Center for Experimental Electrical and Control Engineering Education Lanzhou University of Technology Lanzhou China College of Computer and Communication Lanzhou University of Technology Lanzhou China

Heart rate variability (HRV) extracted from the electrocardiogram (ECG) is an essential indicator for assessing the autonomic nervous system in clinical. Some scholars have studied the feasibility of pulse rate variability (PRV) instead of HRV. However, there is little qualitative research in different body states. In this paper, the photoplethysmography (PPG) of postauricular and finger and the ECG of fifteen subjects were synchronously collected for comparative analysis. The eleven experiments were designed according to the daily living state, including the stationary state, limb movement state, and facial movement state. The substitutability of nine variables was investigated in the time, frequency, and nonlinearity domain by Passing Bablok regression and Bland Altman analysis. The results showed that the PPG of the finger was destroyed in the limb movement state. There were six variables of postauricular PRV, which showed a positive linear relationship and good agreement (p > 0.05, ratio (Formula presented.) 0.2) with HRV in all experiments. Our study suggests that the postauricular PPG could retain the necessary information of the pulse signal under the limb movement state and facial movement state. Therefore, postauricular PPG could be a better substitute for HRV, daily PPG detection, and mobile health than finger PPG. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Photoplethysmography

来源：评论

学校读者我要写书评

暂无评论

Study on Fluctuation Characteristics of Acoustic Signals under Density Layered Fluid Disturbance

Study on Fluctuation Characteristics of Acoustic Signals und...

引用

2024 OES China Ocean Acoustics, COA 2024

作者： Yong, Jintao Chen, Yunfei Wang, Zhenshan Jia, Bing Wang, Rui Mo, Shiqi Science and Technology on Underwater Test and Control Laboratory Dalian China College of Underwater Acoustic Engineering Harbin Engineering University Harbin China College of Information and Communication Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9798350340297

This study investigates the fluctuation characteristics of acoustic signals in the presence of flow field perturbations within density-stratified fluids through laboratory simulation experiments. A density stratification tank was used to replicate the ocean's stratified environment. The SUBOFF scaled model was employed to mimic the underwater vehicle's navigation process in towing mode. controlled density stratification simulation experiments were conducted to explore the acoustic signal fluctuation characteristics within the wake flow field of the submerged model. Data on the undulation properties of acoustic signals that propagated through the wake flow field of the underwater vehicle were collected. The undulation characteristics of the acoustic signal at two towing speeds and various spatial positions were analyzed. In alignment with the typical marine environment characteristics, this study designed the stratification conditions, the scale of the scaled model, and the towing speed based on the Froude number (Fri) similarity criterion and the geometric similarity law. The analysis of the experimental results indicates that the fluctuating frequency of the acoustic signal amplitude diminishes over time as the wake dissipates post-target passage. Concurrently, the intensity of the high-frequency fluctuation component of the signal also decreases with the dissipation of the wake. © 2024 IEEE.

关键词： Wakes

来源：评论

学校读者我要写书评

暂无评论

Multi Modal EEG-Based Classification of Alzheimer's Disease and Mild Cognitive Impairment Using Hilbert Huang Transform

Multi Modal EEG-Based Classification of Alzheimer's Disease ...

引用

2024 International Conference on Advances in Modern Age Technologies for Health and engineering Science, AMATHE 2024

作者： Gopu, G. Sathish, S. Shanmathan, T.S. Suthakar, G. Sivakumaran, N. Geetha Devasena, M.S. Sri Ramakrishna Engineering College Electronics And Communication Engineering Coimbatore India National Institute Of Technology Instrumentation And Control Engineering Tiruchirappalli India Sri Ramakrishna Engineering College Computer Science And Engineering Coimbatore India

ISBN: (纸本)9798350371567

This study investigates whether high-resolution brain-functional connectivity, which is measured by using Electroencephalography (EEG) combined with Hilbert Huang Transform (HHT) can be useful in Alzheimer Disease Diagnosis. The major issue with Alzheimer's disease (AD) is that it leads to cognitive decline and affects millions of people worldwide. Early prediction of the disease is mandatory and crucial for timely intervention and effective care. EEG signals, a non-invasive and cost-effective method to assess brain activity, have shown potential in predicting this disease. In this study, we propose an approach that utilizes EEG data combined with Hilbert-Huang Transform (HHT) and machine learning algorithms for classification which is a novelty of the study that enables early prediction of Alzheimer's disease. Our methodology was tested on a dataset comprising EEG signals recorded using 19 electrodes from both healthy individuals and patients with Alzheimer's and the Mild Cognitive Impairment (MCI). The results were promising, demonstrating high accuracy, sensitivity, and specificity. Machine learning techniques can be employed for categorizing EEG signals, but it essential to validate their effectiveness using large and diverse datasets. This research highlights the potential of HHT and EEG data in the prediction of this disease. Principal Component Analysis (PCA) is used for dimensional reduction of the dataset. Notably EEG signals combined with Hilbert Huang Transform and Principal Component Analysis gives better accuracy of 98.6% for KNN. This research highlights the potential of EEG analysis combined with advanced techniques for accurate classification of dementia-related disorders. © 2024 IEEE.

关键词： Empirical mode decomposition

来源：评论

学校读者我要写书评

暂无评论

Optimizing Performance in Automatic Powder Filling Systems 4

Optimizing Performance in Automatic Powder Filling Systems

引用

4th International Conference on Power, Energy, control and Transmission Systems, ICPECTS 2024

作者： Mohanraj, K. Ramesh, A. Vairavel, K.S. Mohammed Thoufik, S. Muthuraja, R. Mohamed Arshad, M. Sri Sairam Engineering College Department of Instrumentation & Control Engineering Chennai India Sri Eshwar College of Engineering Department of Electronics and Communication Engineering Coimbatore India Bannari Amman Institute of Technology India

ISBN: (纸本)9798331508845

There have been crucial changes in the packaging industry recently, especially with regard to Form Fill and Seal (FFS) machines. These machines can be found in different sizes making them available for use by small businesses that want to lower their plant costs using inexpensive automated packaging solutions. This paper describes a low-cost weighing and pouring mechanism for improving accuracy of pouch filling machine. The process flow is carefully designed so as to achieve optimum production rates. Manipulators under the control of our mechatronics system are regulated through feedback from sensors managed by microcontroller. © 2024 IEEE.

关键词： Costs

来源：评论

学校读者我要写书评

暂无评论

Deterministic Event-Based Physical Watermarks Against Replay Attacks in Cyber-Physical Systems

IEEE Transactions on Industrial Cyber-Physical Systems

引用

IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 61-69页

作者： Zhao, Xudong Xing, Wei Zhang, Junfeng Wang, Xinyu Zong, Guangdeng Zhao, Ning Hainan University School of Information and Communication Engineering Haikou570288 China Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education Dalian116622 China Tiangong University School of Control Science and Engineering Tianjin300387 China Bohai University College of Control Science and Engineering Jinzhou121013 China

Cyber-physical systems (CPSs) are of great importance in various applications and have garnered significant attention. Ensuring their security is a crucial concern, while this paper focuses on the security of CPSs against replay attacks during the transmission of sensor measurements over a wireless network. It is widely recognized that incorporating physical watermark signals is an effective approach to mitigate replay attacks. However, traditional physical watermarks are time-based and result in a notable degradation in the performance of Linear Quadratic Gaussian systems. With this in mind, a novel event-based physical watermarking technique is devised to address the performance degradation and detect replay attacks. The approach involves a deterministic physical watermark schedule that utilizes the innovation sequence to determine whether to incorporate physical watermarks or not. We provide evidence that the probability of successfully embedding physical watermarks increases when the system is targeted by malicious attacks. Additionally, we demonstrate that the deterministic event-based watermarking approach is more effective than the traditional time-based watermarking method. Finally, simulation examples are included to validate and illustrate the theoretical results. © 2023 IEEE.

关键词： Cyber attacks

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：