检索结果-内蒙古大学图书馆

15th International Conference on Communication Software and Networks, ICCSN 2023

作者： Zhang, Feiqing Yin, Zhenyu Li, Jiong Xu, Guangyuan Xu, Fulong Chinese Academy of Sciences Shenyang Institute of Computing Technology China University of Chinese Academy of Sciences China Liaoning Key Lab. of Domestic Industrial Control Platform Technology on Basic Hardware Software Shenyang110168 China

ISBN: (纸本)9798350329360

Fault diagnosis is crucial for the safe operation of rotating machinery. Existing rolling bearing fault diagnosis algorithms generally have low accuracy in the presence of noise, and there are issues with complex algorithm structures and high computational complexity. Therefore, this paper researches rolling bearing fault diagnosis using a lightweight residual network. First, the signals are preprocessed using the short-time Fourier transform to highlight the impact features of the vibration signals. Then, a lightweight residual network based on channel attention is designed to focus on the impact features of faults, effectively improving the algorithm's ability to extract nonlinear features. Finally, experimental results demonstrate that the proposed algorithm can effectively solve the problem of rolling bearing fault diagnosis in noisy and multi-load environments, with low computational complexity and model size. © 2023 IEEE.

关键词： Failure analysis

来源：评论

学校读者我要写书评

暂无评论

Research on Power Load Forecasting Based on Deep Learning 3

Research on Power Load Forecasting Based on Deep Learning

引用

3rd International Conference on Consumer Electronics and Computer Engineering, ICCECE 2023

作者： Lin, Lanxin Yao, Jingxin Wang, Kun Zhejiang Gongshang University Sussex Artificial Intelligence Institute Hangzhou310000 China Northeastern University at Qinhuangdao School of Control Engineering Qinhuangdao Hebei066000 China University of Chinese Academy of Sciences Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang110168 China

ISBN: (纸本)9798350331578

In order to fully explore the time-series correlation of power load data and improve the prediction accuracy of power load, this paper proposes a neural network-based deep learning approach for power load prediction. Firstly, the relevant electric power data are obtained and divided into appropriate sample sizes, and the samples are normalized;then, a prediction model based on LSTM is built to explore the correlation between different features, and the corresponding model of this neural network is further trained and validated on the data test set;finally, a comparison between LSTM and other algorithms such as SVM, ANN, GAOS and GM are performed. The results show that the LSTM prediction algorithm can better track the trend of power load change, with higher prediction accuracy and efficiency. © 2023 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

Semi-independent Convolution for Image Inpainting 50

Semi-independent Convolution for Image Inpainting

引用

50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Huang, Wenli Deng, Ye Xin, Xiaomeng Zhao, Zhihong He, Jinbao Wang, Jinjun School of Electronic and Information Engineering Ningbo University of Technology Ningbo China School of Computing and Artificial Intelligence Southwestern University of Finance and Economics Chengdu China Institute of Artificial Intelligence and Robotic Xi’an Jiaotong University Xi’an China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin China School of Electronics and Information Engineering Ningbo University of Technology Ningbo China

ISBN: (纸本)9781665464543

In typical image inpainting tasks, the locations and shapes of damaged or masked areas are often random and irregular. Vanilla convolutions, commonly employed in learning-based inpainting models, treat all spatial features as valid and share parameters across different regions. This approach can struggle with irregular damage patterns, leading to inpainted results that may suffer from color discrepancies and blurriness. In this paper, we introduce a novel operator known as Semi-Independent Convolution (SIConv) to tackle this challenge. The proposed SIConv, on top of the regular convolution with shared weights, also introduces dynamic terms that assign their own independent weights to each part of the image, and the overall computation is formulated as a shared convolution parameter with an additional term to describe the local structure. Qualitative and quantitative experiments demonstrate that our method outperforms the state-of-the-art, yielding clearer, more coherent, and visually convincing inpainting results. © 2024 IEEE.

关键词： convolution Image inpainting semi-independent

来源：评论

学校读者我要写书评

暂无评论

High-Altitude Balloons No-Fly Zone Avoidance Based Reinforcement Learning

High-Altitude Balloons No-Fly Zone Avoidance Based Reinforce...

引用

2024 IEEE International Conference on Real-Time computing and Robotics, RCAR 2024

作者： Liu, Jinkua Li, Xiaotao Hu, Yu Zhang, Bo Georgia Institute of Technology College of Computing AtlantaGA30332 United States Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China Shenzhen518107 China Shenzhen City Joint Laboratory of Autonomous Unmanned Systems and Intelligent Manipulation Shenzhen518060 China

ISBN: (纸本)9798350372601

High-altitude balloons are commonly used in scientific research but have challenges in operation due to underactuation and non-linear dynamics affected by atmospheric factors, resulting in traditional model-based control impractical. In response, reinforcement learning (RL) has been utilized as a promising approach for balloon control, achieving breakthroughs in station-keeping and navigation. Nonetheless, the No-Fly Zone (NFZ) avoidance of high-altitude balloons remains a largely uncharted territory. This study adopts a reinforcement learning-based methodology to address this particular problem. Quantile Regression DQN and DQN methods are utilized to guarantee the efficiency evaluated through simulating diverse NFZ configurations and missions. Results demonstrate that this approach effectively avoids NFZs, underscoring RL's potential to enhance the safety and efficiency of high-altitude balloon operations. © 2024 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Distributed Malicious Maneuvering Target Tracking Algorithm with Finite-Time Fusion Analysis 42

Distributed Malicious Maneuvering Target Tracking Algorithm ...

引用

42nd Chinese control Conference, CCC 2023

作者： Zhang, Zheng Guo, Dong Zheng, Hongwei Wang, Hong Li, Qingdong Dong, Xiwang Ren, Zhang School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China China Academic of Launch Vehicle Technology Beijing100076 China Beijing Academy of Blockchain and Edge Computing Beijing100871 China Beijing Institute of Control Engineering Beijing100094 China Institute of Artificial Intelligence Beihang University Beijing100191 China

ISBN: (纸本)9789887581543

This paper proposes a distributed tracking framework for high-maneuvering and malicious maneuvering target based on the sensor network. Considering some of sensors in the network can only observe partial system output, the collective observability is guaranteed. Based on the collective observability, the distributed target tracking algorithm is designed by local filter phase and consensus fusion phase. In local filter phase, the local estimate results can be obtained by each sensor node. Based on the target kinematic and sensor observation equations, the Kalman-like estimation algorithm is proposed to obtain the local estimate results. In most of the exist distributed state estimation (DSE) algorithms, the excellent target tracking performance is based on the assumption that the fusion times is infinity in consensus fusion phase. In practical application, however, the consensus fusion phase should be completed during two sampling instants. Besides, based on the finite-time stability theory, the error covariance matrix is processed as the solution of discrete-time algebraic Riccati equation (DARE). Then the stability of the proposed algorithm with finite-time consensus fusion is analyzed. Finally, a numerical example for tracking maneuvering target is given to validate the effectiveness. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Target tracking

来源：评论

学校读者我要写书评

暂无评论

Hadron productions and jet substructures associated with Z^(0)/γ in Pb+Pb collisions at the LHC

引用

Science China(Physics,Mechanics & Astronomy) 2023年第12期66卷 77-89页

作者： Shan-Liang Zhang Hongxi Xing Ben-Wei Zhang Key Laboratory of Atomic and Subatomic Structure and Quantum Control(MOE) Guangdong Basic Research Center of Excellence for Structure and Fundamental Interactions of MatterInstitute of Quantum MatterSouth China Normal UniversityGuangzhou 510006China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Guangdong Provincial Key Laboratory of Nuclear ScienceSouthern Nuclear Science Computing CenterSouth China Normal UniversityGuangzhou 510006China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Southern Nuclear Science Computing CenterSouth China Normal UniversityGuangzhou 510006China Institute of Particle Physics and Key Laboratory of Quarks and Lepton Physics(MOE) Central China Normal UniversityWuhan 430079China

We carry out a detailed study of medium modifications on Z^(0)/γ+hadron correlations as well as jet substructures in association with Z^(0)/γ in Pb+Pb collisions with √S_(NN)=5.02TeV at the *** utilize the linear Boltzmann transport(LBT)model to simulate the jet-medium interactions and medium response,and an extended cluster hadronization model to investigate the nonperturbative transition of quarks and gluons into final hadrons in heavy-ion *** hadronization effect,we can well describe Z^(0)/γ+hadrons correlations and Z^(0)/γ-tagged jet substructures in both p+p and Pb+Pb collisions *** modification on jet profile and jet fragmentation functions indicate that particles carrying a large fraction of the jet momentum are generally closely aligned with the jet axis,whereas low-momentum particles are observed to have a much broader angular distribution relative to jet axis in Pb+Pb collisions due to jet-medium *** particular,we find that Z^(0)/γ-tagged hadron correlations are sensitive to the soft particles from the dense medium and medium response,while jet-substructures show weak dependence on those soft hadrons with only a fraction of them falling inside the jet area.

关键词： relativistic heavy-ion collisions jet quenching hadronization jet substructures

来源：评论

学校读者我要写书评

暂无评论

Improved K-means Algorithm for Fault Diagnosis of Vehicle 9

Improved K-means Algorithm for Fault Diagnosis of Vehicle

引用

9th International Conference on Computer and Communications, ICCC 2023

作者： Yang, Dongsheng Xie, Jiawei Yin, Zhenyu Chinese Academy of Sciences Shenyang Institute of Computing Technology Shenyang China University of Chinese Academy of Sciences Shenyang China Liaoning Key Lab. of Domestic Industrial Control Platform Technology on Basic Hardware and Software Shenyang China

ISBN: (纸本)9798350317251

This paper aims to improve the accuracy of anomaly data identification in fault diagnosis of vehicle using an improved K-means clustering algorithm. To address the sensitivity of initial cluster centroids and the tendency to fall into local optima when identifying anomaly data with traditional K-means clustering algorithms, we propose an IDBO-Kmeans clustering algorithm for vehicle fault diagnosis. The algorithm is based on the original Dung Beetle Optimization algorithm and introduces three optimization strategies: chaotic mapping, adaptive boundary adjustment, and random walk, to improve the quality of initial cluster centroids. The optimized initial cluster centroid are then used with the K-means algorithm for further clustering. Experimental results show that IDBO-Kmeans improves the accuracy of anomaly data identification in vehicle fault diagnosis and addresses the limitations of traditional K-means clustering. © 2023 IEEE.

关键词： Failure analysis

来源：评论

学校读者我要写书评

暂无评论

Flexible production line product R&D and manufacturing cloud platform based on intelligent data collaboration 3

Flexible production line product R&D and manufacturing cloud...

引用

3rd International Seminar on Artificial Intelligence, Networking, and Information Technology, AINIT 2022

作者： Xie, Yanyin Yang, Rui Hu, Ruihan Gan, Lin Ke, Hualin Guangdong HEGII Sanitary Wares Co. Ltd Chaozhou528000 China Guangdong Institute of Intelligent Manufacturing Guangdong Key Laboratory of Modern Control Technology Guangzhou510070 China Faculty of Computing National Pilot School of Software Harbin Institute of Technology Harbin150000 China

ISBN: (纸本)9781510662964

This paper focuses on how to ensure the availability and effectiveness of massive cloud data for industrial robots in the flexible production line, address the technical challenge in building a massive data cloud platform for industrial robots, and resolve the engineering problem of cloud based industrial robot cloud service application. To achieve this purpose, research is conducted on industrial robot hybrid cloud platform architecture, network technology, industrial robot big data system, autonomous learning cloud data processing and other technologies, which provides support for cloud service applications. It is suggested to combine knowledge atlas, digital twins, deep neural network, migration learning and other artificial intelligence technologies, which is conducive to remote monitoring and fault diagnosis cloud service applications. This has been verified and promoted in the handling, polishing, stacking, welding, assembly and other robots in 3C, mold, household appliances, automobile, furniture, electronic equipment manufacturing and other industries. © 2023 SPIE.

关键词： Industrial robots

来源：评论

学校读者我要写书评

暂无评论

Complex Permeability Determination for EE Core Based on Flexible PCB Fixture and Magnetic Flux Path Length Analysis 2

Complex Permeability Determination for EE Core Based on Flex...

引用

2nd China Power Supply Society Electromagnetic Compatibility Conference, CPEMC 2024

作者： Jie, Huamin Zhao, Zhenyu Chang, Yongqi Wang, Changdong Jiang, Shiqi Gao, Richard Xian-Ke See, Kye Yak School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore Department of Electrical and Computer Engineering National Univeristy of Singapore Singapore Singapore Department of Control Science and Engineering Harbin Institute of Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China Institute of High Performance Computing A*STAR Singapore Singapore

ISBN: (纸本)9798331509552

The complex permeability of magnetic cores acts as a vital factor in electromagnetic interference (EMI) filtering choke design and optimization. Many efforts have been reported for toroid cores, but fewer target those with other shapes, such as EE, EI, UU, and UI cores. Owing to their commonly used in planar EMI filters, determining the complex permeability of them is of significance. Targeting EE cores, this paper presents a flexible printed circuit board (PCB)-based fixture adapter tailored designed for performing the measurement, while the corresponding core permeability can be calculated through magnetic flux path length analysis. The experiments validate the effectiveness and accuracy of the proposed methods, spanning a wide frequency range up to 120 MHz. ©2024 IEEE.

关键词： Magnetic flux

来源：评论

学校读者我要写书评

暂无评论

Optimizing Human Activity Recognition Using Stacked CNN with Ensemble Learning

引用

Procedia Computer Science 2025年 258卷 1598-1607页

作者： Divya Yadav Deepika Rani Om Parakash Verma Department of Mathematics and Computing Dr B R Ambedkar National Institute of Technology Jalandhar Jalandhar Punjab India Department of Instrumentation and Control Engineering Dr B R Ambedkar National Institute of Technology Jalandhar Jalandhar Punjab India

In recent times, Human Activity Recognition (HAR) plays a crucial role in numerous artificial intelligence applications, including surveillance, healthcare, and security. However, the primary challenges in accurately identifying human activities from video data include occlusion, low resolution, data scarcity, and high computational costs. The main objective of this study is to enhance both the recognition accuracy and computational efficiency. This study presents a computationally efficient HAR model that leverages deep learning and machine learning algorithms for feature extraction and classification tasks. The proposed model consists of three fine-tuned convolution neural networks: VGG16, VGG19, and MobileNetV2 for feature extraction, combined with four classifiers, Support Vector Machine (SVM), Random Forest (RF), Multilayer Perceptron (MLP), and Fuzzy classifier. The performance of the proposed model was evaluated using three benchmark datasets: KTH, YouTube11, and Peliculas. The proposed method demonstrated exceptional performance of 99.60% and 99.50% accuracy on the KTH and Peliculas dataset using MobileNet and SVM. Additionally, the proposed method achieved a superior performance of 99.80% on the YouTube11 dataset with a combination of VGG16 and SVM. Finally, the performance of the proposed model was compared and validated against previous models.

关键词： Human Activity Recognition (HAR) Convolution Neural Network (CNN) Feature Extraction Classification

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：