检索结果-内蒙古大学图书馆

Journal of Network Intelligence 2024年第2期9卷 658-672页

作者： Hou, Xiao-Mao Cai, Liu-Ping Wang, Yan-Hui Automation and Information Engineering College Hunan Chernical Vocational Technology College Zhuzhou412000 China Graduate School Department Saint Paul University Tuguegarao3500 Philippines School of Computer Science and Engineering Hunan University of Information Technology Changsha410151 China

Image fuzzy enhancement is a research hotspot in the field of image processing, which aims to recover enhanced beginning clear images from degraded images. Based on the research of traditional particle swarm optimization algorithm and fuzzy enhancement algorithm, an image fuzzy enhancement method based on membrane computing particle swarm algorithm is proposed. Firstly, in order to make full use of the sparse characteristics of the clear image, the coefficient decomposition under wavelet domain and tightly supported wavelet domain is performed on the image respectively. Then, a joint optimisation model is constructed using L1 parametric constraints to achieve pretzel noise cancellation. Next, the MMH-PSO algorithm is designed by improving the particle swarm algorithm using membrane computing and Metropolis-Hastings sampling. Based on the simulated annealing algorithm temperature drop process, Metropolis-Hastings sampling is used to add randomness to the particle swarm algorithm so that it has the ability to jump out of the local optimum. The use of membrane computing enhances the parallelism of the particle swarm algorithm and can reduce the time complexity in solving complex problems. Finally, MMH-PSO is used to simultaneously search out the magnitude of the two fuzzy parameters in the traditional fuzzy enhancement algorithm in order to improve the accuracy of the algorithm. The experimental results show that the proposed algorithm has better SSIM values than the traditional fuzzy enhancement algorithm, which effectively improves the image quality and makes the image edge information more abundant. © 2024, J. Network Intell. All rights reserved.

关键词： Simulated annealing

来源：评论

学校读者我要写书评

暂无评论

A Real-Time Semantic Segmentation Method Based on Transformer for Autonomous Driving

引用

computers, Materials & Continua 2024年第12期81卷 4419-4433页

作者： Weiyu Hao Jingyi Wang Huimin Lu Donald Bren School of Information and Computer Sciences University of CaliforniaIrvineCA 92612USA Department of Control Engineering Kyushu Institute of TechnologyKitakyushu804-8550Japan School of Automation Southeast UniversityNanjing210096China

While traditional Convolutional Neural Network(CNN)-based semantic segmentation methods have proven effective,they often encounter significant computational challenges due to the requirement for dense pixel-level predictions,which complicates real-time *** address this,we introduce an advanced real-time semantic segmentation strategy specifically designed for autonomous driving,utilizing the capabilities of Visual *** leveraging the self-attention mechanism inherent in Visual Transformers,our method enhances global contextual awareness,refining the representation of each pixel in relation to the overall *** enhancement is critical for quickly and accurately interpreting the complex elements within driving sce-narios—a fundamental need for autonomous *** experiments conducted on the DriveSeg autonomous driving dataset indicate that our model surpasses traditional segmentation methods,achieving a significant 4.5%improvement in Mean Intersection over Union(mIoU)while maintaining real-time *** paper not only underscores the potential for optimized semantic segmentation but also establishes a promising direction for real-time processing in autonomous navigation *** work will focus on integrating this technique with other perception modules in autonomous driving to further improve the robustness and efficiency of self-driving perception frameworks,thereby opening new pathways for research and practical applications in scenarios requiring rapid and precise decision-making *** experimentation and adaptation of this model could lead to broader implications for the fields of machine learning and computer vision,particularly in enhancing the interaction between automated systems and their dynamic environments.

关键词： Visual transformer semantic segmentation autonomous driving

来源：评论

学校读者我要写书评

暂无评论

Analysis of Predictive Current Regulator for High-Speed IPMSM Operating at Low Sampling to Fundamental Frequency Ratios 26

Analysis of Predictive Current Regulator for High-Speed IPMS...

引用

26th International Conference on Electrical Machines and Systems, ICEMS 2023

作者： Lin, Shengyu Mon-Nzongo, Daniel L. Ipoum-Ngome, Paul G. Lai, Chunyan Fuzhou University College of Electrical Engineering and Automation Fuzhou China Concordia University Department of Electrical and Computer Engineering Concordia Canada

ISBN: (纸本)9798350317589

At low sampling to fundamental frequency ratios, the time delay introduced by the Pulse Width Modulation (PWM) calculation and the duty cycle update deteriorates the decoupling dynamic between d and q-axis currents. The controllers implemented with One-step Current Prediction (OCP) method can reduce the effects of PWM delay. But, inappropriate tuning of the control parameters will lead to poor dynamic responses and less stability. Therefore, a comprehensive analysis and tuning approach are proposed in this paper, for the PI and the Internal Model Controller (IMC) with the OCP. In addition, an active resistance for the Interior Permanent Magnet Synchronous Motors (IPMSM) is designed and implemented in IMC to enhance the disturbance rejection capabilities. This paper introduces the root locus to select the correct parameter with better dynamic response and stability. With OCP and active resistance, the IMC controller obtains an improved dynamic response and stability at a minimum sampling ratio of 5. Simulation results performed at various conditions have successfully validated this study. © 2023 IEEE.

关键词： Pulse width modulation

来源：评论

学校读者我要写书评

暂无评论

Human novel pose generation with pose optimization and importance sampling based on NeRF 16

Human novel pose generation with pose optimization and impor...

引用

2024 16th International Conference on Graphics and Image Processing, ICGIP 2024

作者： Li, Ke Zhang, Binbin Su, Zhiyong Li, Weiqing School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China School of Automation Nanjing University of Science and Technology Nanjing China

ISBN: (数字)9781510688780

ISBN: (纸本)9781510688773

The Neural Radiance Field (NeRF) method has emerged as a groundbreaking technique for human reconstruction, enabling the generation of high-quality, photorealistic rendering of reconstructed objects. Despite its promising results, several challenges persist, particularly when it comes to generalizing to unknown poses during the generation of virtual human animations. This paper proposes a method for generating and optimizing novel human poses based on NeRF. Given that existing pose-driven NeRF methods heavily rely on the accuracy of SMPL body parameters, we implemente human pose optimization based on motion capture data as prior knowledge, resulting in more accurate SMPL parameters, which contributes to a more precise human canonical model. Additionally, we propose a pose-driven deformation field based on linear blend skinning, combining blend weight fields with the 3D human skeleton to achieve precise mapping from observed poses to the canonical pose. By estimating the camera ray transmittance distribution during volume rendering, we propose importance sampling method avoiding sampling points in free space, which further improves rendering quality. Extensive experiments demonstrate that our method yields significant improvements in rendering quality for both training poses and novel poses, as evidenced by results on the ZJU-MoCap dataset and our custom dataset. This work not only advances the capabilities of NeRF in human reconstruction but also opens new avenues for realistic virtual human animation. © 2025 SPIE.

关键词： Motion capture

来源：评论

学校读者我要写书评

暂无评论

Optimization Operation Strategy of Integrated Energy System Considering Load Flexibility and Energy Conversion Device

Optimization Operation Strategy of Integrated Energy System ...

引用

International Conference of Electrical, Electronic and Networked Energy Systems, EENES 2024

作者： Du, Yu Yu, Yekun School of Automation and Electrical Engineering Linyi University Linyi276000 China School of Computer Electronics and Information in Guangxi University Nanning530004 China

ISBN: (纸本)9789819620456

Flexible load can actively participate in the operation control of the integrated energy system and interact with the integrated energy system. Flexible load scheduling and regulation is one of the important means to alleviate the contradiction between power supply and demand and realize the effective consumption of renewable energy. This paper presents an integrated energy system optimization strategy considering load flexibility and equipment with energy conversion characteristics. The strategy aims to improve the efficiency and flexibility of the system by optimizing the scheduling of energy production, storage and consumption within the community. At the same time, the flexible adjustment ability of the flexible load is used to adjust the real-time carbon emission economic penalty of the operator and the peak reduction economic compensation of the LAs, so as to achieve the purpose of energy saving and carbon reduction, so as to achieve the purpose of low-carbon operation of the comprehensive energy system. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Zero-carbon

来源：评论

学校读者我要写书评

暂无评论

A Novel Deep Learning Model for Classifying Power Quality Problems in PV-integrated Microgrids using CNN-LSTM 1

A Novel Deep Learning Model for Classifying Power Quality Pr...

引用

1st International Conference on Innovative engineering Sciences and Technological Research, ICIESTR 2024

作者： Channa, Irfan Ali Li, Dazi Dahri, Fida Hussain Abro, Ghulam E. Mustafa Zahid, Faizan University of Chemical Technology Institute of Automation Beijing Beijing100069 China Southeast University School of Computer Science and Engineering Nanjing China Saudi Arabia University of Catania Department of Electrical Electronic and Computer Engineering Italy

ISBN: (纸本)9798350348637

Distributed generation based on photo-voltaic (PV) modules play a vital role to provide continuous power supply for consumers. Power quality (PQ) events caused by integration of distributed energy sources in microgrids (MG) deteriorate the operation of distribution and utility of power supply. In this work, a new CNN-LSTM based deep learning approach is proposed to identify power quality disturbances (PQDs) in PV-integrated microgrid. In a proposed framework, full closed-loop neural architecture containing different layers to facilitate automatic feature extraction and long-time short memory (LSTM) network provide temporal feature for intelligent classifier to improve the training speed. Moreover, comparison with other deep neural networks proves that proposed approach can simplify the procedure of PQ problems with the conventional signal analysis and feature selection methods. A typical PV-integrated microgid is simulated on PSCAD software to prove the robustness of classifier for classification of PQDs in renewable energy integrated distribution networks. © 2024 IEEE.

关键词： Microgrids

来源：评论

学校读者我要写书评

暂无评论

Event-Triggered Fixed-Time Adaptive Fuzzy Control for Nontriangular Nonlinear Systems With Unknown Control Directions

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第5期5卷 2397-2409页

作者： Cui, Guozeng Xu, Hui Yu, Jinpeng Ma, Qian Jian, Muwei Suzhou University of Science and Technology School of Electronic and Information Engineering Suzhou215009 China Qingdao University School of Automation Qingdao266071 China Nanjing University of Science and Technology School of Automation Nanjing210094 China Shandong University of Finance and Economics School of Computer Science and Technology Jinan250014 China

This article focuses on the problem of fixed-time adaptive fuzzy control for a class of nontriangular nonlinear systems with unknown control directions under the event-triggered framework. To tackle the algebraic loop issue arising from the nontriangular structure, the property of the fuzzy logic system is employed. The command filter and the error compensation signals, which have the feature of fixed-time convergence, are constructed to eliminate the 'explosion of complexity' phenomenon and the effect of filtered error, respectively. By integrating the Nussbaum gain technique into the relative threshold-based event-triggered mechanism, a singularity-free fixed-time adaptive fuzzy control scheme is devised to ensure that the closed-loop system is practically fixed-time stable, and the tracking error converges to a small region near the origin in a fixed time. Finally, simulation examples are presented to demonstrate the effectiveness and superiority of the proposed fixed-time control algorithm. © 2020 IEEE.

关键词： Backstepping

来源：评论

学校读者我要写书评

暂无评论

An approach of occlusion perception based on knowledge distillation in complex vineyard environment

An approach of occlusion perception based on knowledge disti...

引用

2024 International Conference on Algorithms, High Performance Computing, and Artificial Intelligence, AHPCAI 2024

作者： Zhao, Jingxian Wang, Jinhai Lin, Xuemin Chen, Mingyou Wei, Huiling Luo, Lufeng School of Computer Science and Artificial Intelligence Foshan University Foshan China School of Mechatronic Engineering and Automation Foshan University Foshan China

ISBN: (纸本)9781510685840

To address the challenges of occlusion in intelligent picking within unstructured environments, this paper proposes an occlusion perception algorithm utilizing knowledge distillation. A grape occlusion dataset was developed to support the study. The proposed method employs a lightweight MobileNetV3 student model, trained under the supervision of a high-accuracy ResNet50 teacher model, to achieve comparable performance with significantly fewer network parameters. Experimental results demonstrate that the knowledge-distilled student model operates with only 1.50% of the teacher model's operations while achieving an accuracy of 99.4%, representing a 2.4% improvement over the baseline model. These findings underscore the method's effectiveness in developing efficient, high-performance models suitable for deployment in resource-constrained environments. © 2024 SPIE.

关键词： Wine

来源：评论

学校读者我要写书评

暂无评论

Performance-Guaranteed Finite-Time Tracking of Strict-Feedback Systems with Unknown Control Directions: A Novel Switching Mechanism

引用

IEEE Transactions on Automatic Control 2025年第6期70卷 4061-4068页

作者： Mao, Bing Wu, Xiaoqun Fan, Ziye Lu, Jinhu Chen, Guanrong Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China Wuhan University School of Mathematics and Statistics Hubei430072 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China City University of Hong Kong Department of Electrical Engineering Hong Kong Hong Kong

The problem of achieving performance-guaranteed finite-time exact tracking for uncertain strict-feedback nonlinear systems with unknown control directions is addressed. A novel logic switching mechanism with monitoring functions is designed to deal with unknown control directions. This approach is different from existing methods like the Nussbaum gain technique and smooth orientation functions, which are inapplicable to finite-time exact tracking. The main challenge lies in designing monitoring functions and determining switching rules, which is well resolved through three steps. Most significantly, in contrast to existing works that solely guarantee bounded tracking or asymptotic exact tracking, the new mechanism incorporates novel integral sliding mode techniques to achieve finite-time exact tracking with guaranteed performance. Finally, simulations are presented with comparison to demonstrate the effectiveness of the proposed methods. © 1963-2012 IEEE.

关键词： Feedback

来源：评论

学校读者我要写书评

暂无评论

Obstacle avoidance parking based on improved deep reinforcement learning SAC algorithm

Obstacle avoidance parking based on improved deep reinforcem...

引用

2024 China automation Congress, CAC 2024

作者： Liu, Ting Liu, Ping Liu, Mingjie Piao, Changhao Chang, Kyunghi College of Automation Chongqing University of Posts and Telecommunications Chongqing China Electrical and Computer Engineering Department Inha University Incheon Korea Republic of

ISBN: (纸本)9798350368604

Recent research uses neural-network-based approaches to generate time-optimized parking trajectories in linear time. However, the generalization of these neural networks in different parking lot scenarios is not fully considered and relies on high-quality data. To address these issues, this paper proposes an improved soft actor critic (SAC)based parking trajectory planning method to achieve fast convergence and high success rate. A trajectory data-based reward function and an experience replay sampling strategy are designed simultaneously improve the learning efficiency. Meanwhile, the Flatten-T Swish Plus (FTSPlus) activation function is firstly introduced into the SAC's neural network structure to enhance the convergence capabilities. The simulation results show that compared with traditional SAC methods, the success rate has been greatly improved and convergence rate has also been improved by more than 60%. Furthermore, it has the good model generalization ability while maintaining collision-free trajectories. © 2024 IEEE.

关键词： Trajectories

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：