检索结果-内蒙古大学图书馆

26th International Conference on Industrial Technology, ICIT 2025

作者： Chen, Yiheng Yin, Fan Chen, Xiaochong Ren, Yi Hu, Jie Wu, Min School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9798331521950

The sccheduling for pushing plan during the coking process critically affects the efficiency and stability of production. However, the complexity with mutiple-stage during production makes it difficult to design an efficient coke pushing plan. To address this issue, this paper proposes a scheduling method based on the particle swarm optimization algorithm. Firstly, the fuzzy c-means clustering is utilized to categorize actual operating conditions as either normal or abnormal, thereby facilitating the scheduling of pushing plan under disparate conditions. Subsequently, the scheduling problem for the pushing plan is transformed into a traveling salesman problem, and scheduling models under various conditions are established. Finally, to accelerate the convergence and enhance the algorithm's global search capability, an adaptive inertia adjustment strategy is employed to dynamically regulate the velocity and position of particles. The proposed method has been implemented in the coking process. Through the analysis of application results, the completion coefficient of pushing plan has been increased by 4.25%, demonstrating that the proposed has advantages in scheduling the pushing plan during the actual coking process. © 2025 IEEE.

关键词： Particle swarm optimization (PSO)

来源：评论

学校读者我要写书评

暂无评论

The Innovative Multi-Cavity Pneumatic Actuator: A Chemical Reaction-Driven Device for Generating Mechanical Crawling Motion

The Innovative Multi-Cavity Pneumatic Actuator: A Chemical R...

引用

Robotics, control and automation (ICRCA), International Conference on

作者： Junqi Mu Yiyang Wei Xiaofeng Zong School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

ISBN: (数字)9798331544577

ISBN: (纸本)9798331544584

The low manufacturing cost and fast response speed of pneumatic actuators have attracted widespread attention from researchers in the field of soft robotics. Biomimetic design, as one of the mainstream design concepts of pneumatic actuators, has provided researchers with a source of inspiration. Most existing actuators are based on biomimetic design. In this paper, a pneumatic soft actuator with a biomimetic worm-like design for crawling robots is proposed. This actuator is composed of multiple mesh-like air chambers, and its main parameters are optimized through finite element analysis, enabling it to perform various complex movements. Moreover, in most existing pneumatic actuators, the air source is supplied by air pumps, while the designed actuator in this paper is powered by chemical reactions. By controlling the types and ratios of raw materials, different chemical reactions occur, leading to periodic inhalation and exhalation, allowing the actuator to perform repetitive movements as intended. This driving method can effectively combine with the mechanical motion of the crawling robot, enhancing the autonomy and environmental adaptability of soft robots.

关键词： Pneumatic actuators Performance evaluation Gases Biomimetics Pneumatic systems Soft robotics Chemical reactions Raw materials Manufacturing Finite element analysis

来源：评论

学校读者我要写书评

暂无评论

CDP-GAN:Near-Infrared and Visible Image Fusion Via Color Distribution Preserved GAN

引用

IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1698-1701页

作者： Jun Chen Kangle Wu Yang Yu Linbo Luo the School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex SystemsEngineering Research Center of Intelligent Technology for Geo-ExplorationMinistry of EducationChina University of GeosciencesWuhan 430074China the Shanghai Institute of Technical Physics Key Laboratory of Infrared System Detecting and Imaging TechnologyChinese Academy of SciencesShanghai 200083China the School of Mechanical Engineering and Electronic Information China University of GeosciencesWuhan 430074China

Dear Editor,This letter is concerned with dealing with the great discrepancy between near-infrared(NIR)and visible(VS)image fusion via color distribution preserved generative adversarial network(CDP-GAN).Different from the global discriminator in prior GAN,conflict of preserving NIR details and VS color is resolved by introducing an attention guidance mechanism into the ***。

关键词： details dealing preserving

来源：评论

学校读者我要写书评

暂无评论

Variational Autoencoder Based Network Embedding Algorithm for Protein Function Prediction 2022

Variational Autoencoder Based Network Embedding Algorithm fo...

引用

14th International Conference on Machine Learning and Computing, ICMLC 2022

作者： Cao, Guansong Zhu, Yuan Yi, Ming School of Automation China University of Geosciences China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System China University of Geosciences Wuhan China School of Mathematics and Physics China University of Geosciences Wuhan China

ISBN: (纸本)9781450395700

The development of high-throughput technology has produced a large number of protein-protein interaction datasets, which provide an effective way to infer the functional annotation of proteins. However, how to make proper use of these datasets to extract effective low-dimensional feature representation of proteins for functional prediction is a challenge. Most existing network integration methods for protein function prediction have some limitations to capture complex and highly non-linear network structure information due to their design architecture. Therefore, we propose a novel multi-network embedding method deepVAE based on deep variational autoencoder (VAE), which uses the variational autoencoder to extract low-dimensional features of proteins from multiple various interactive network datasets and then trains a SVM classifier to predict protein function. Particularly, we denoise the original networks before network embedding, thus the new proposed method is called deepVAE-NE. The experiments are conducted on the yeast and human protein-protein interaction datasets and the experimental performance shows that our methods perform better than the other four compared advanced approaches, which greatly improves the accuracy of functional prediction. © 2022 ACM.

关键词： Proteins

来源：评论

学校读者我要写书评

暂无评论

Research on Eigenvalue of Excitation Signal in Nondestructive Testing of Power Transformer Core 1

引用

18th Annual Conference of china Electrotechnical Society, ACCES 2023

作者： Qu, Yinghui Jin, Fang Dong, Kaifeng Cai, Shengwei Gong, Yujia Fan, Fan School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China China Electric Power Research Institute Co. Ltd. Wuhan430074 China

ISBN: (数字)9789819714285

ISBN: (纸本)9789819714278

Transformer is the most critical equipment in the power system. In recent years, secondary silicon steel sheets have been used in the manufacture of transformer cores, which has caused hidden dangers in the quality of transformers. Currently, the main testing method for transformer core materials is disassembly testing, and there is no effective non-destructive testing method. Because magnetic Buckhausen noise (MBN) signals can reflect the internal defects of ferromagnetic components, this paper uses MBN testing methods to conduct non-destructive testing and analysis the side of transformer core silicon steel sheets. In the study of transformer core MBN signals, it was found that the waveform, frequency, amplitude and other parameters of the excitation signal can affect the eigenvalues of the transformer core MBN signal. The effects of excitation signal waveform, frequency, and amplitude on the characteristic values of MBN signals on the side of transformer core silicon steel sheet were experimentally studied. The research results show that when the excitation signal is a square wave with an amplitude of about 5V, excellent MBN signals can be excited. © Beijing Paike Culture Commu. Co., Ltd. 2024.

关键词： Nondestructive examination

来源：评论

学校读者我要写书评

暂无评论

Quantized impulsive consensus of nonlinear Leader-following multi-agent systems 41

Quantized impulsive consensus of nonlinear Leader-following ...

引用

第41届中国控制会议

作者： Gang Li Xiaowei Jiang Le You Xianhe Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education School of Electrical Engineering and Automation Hubei Normal University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This work looks into the quantized impulsive consensus challenges of nonlinear leader-following multi-agent *** graph theory,principle of differential dynamics,logarithmic quantizer,matrix theory,and the Lyapunov function,among other things,are used to investigate the key discoveries on *** appropriate consensus protocols which contain quantized all agents' relative state information and quantized a part of agents' relative state *** the sake of reducing communication consumption and energy,we combine two control strategies and design two control protocols according to the characteristics of quantized control and impulsive *** a series of deductions,we find that under quantized impulsive control,multi-agent systems can achieve consensus as long as certain sufficient conditions are ***,the simulation example demonstrates the validity and correctness of this papers theoretical approach.

关键词： Multi-agent systems Leader-following Quantized impulsive consensus

来源：评论

学校读者我要写书评

暂无评论

Finite-Time Synchronization of Flux-controlled complex-Valued Memristive Neural Networks

Finite-Time Synchronization of Flux-Controlled Complex-Value...

引用

2023 International Conference on Neuromorphic Computing, ICNC 2023

作者： Wang, Yonghuan Wang, Leimin Wu, Genping China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation Wuhan430074 China Wuhan Second Ship Design and Research Institute Wuhan430064 China

ISBN: (纸本)9798350316889

In this paper, by using the flux-controlled memristor model, the finite-time synchronization problem of delayed complex-valued memristive neural networks (MCNNs) is studied. Firstly, according to the proposed memristor model, we model the MCNNs as continuous systems on voltage-flux-time (wp, varpi, t) domain. Then, we design a class of approaches to realize state synchronization between the drive and response systems, and the corresponding synchronization conditions are achieved. Finally, the effectiveness of results is illustrated with the simulations. © 2023 IEEE.

关键词： Memristors

来源：评论

学校读者我要写书评

暂无评论

Distributed Solver for Discrete-Time Lyapunov Equations over Dynamic Networks with Linear Convergence Rate

引用

IEEE Transactions on Cybernetics 2022年第2期52卷 937-946页

作者： Jiang, Xia Zeng, Xianlin Sun, Jian Chen, Jie Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

The problem of solving discrete-Time Lyapunov equations (DTLEs) is investigated over multiagent network systems, where each agent has access to its local information and communicates with its neighbors. To obtain a solution to DTLE, a distributed algorithm with uncoordinated constant step sizes is proposed over time-varying topologies. The convergence properties and the range of constant step sizes of the proposed algorithm are analyzed. Moreover, a linear convergence rate is proved and the convergence performances over dynamic networks are verified by numerical simulations. © 2013 IEEE.

关键词： Convex optimization

来源：评论

学校读者我要写书评

暂无评论

Decomposing Visual and Semantic Correlations for Both Fully Supervised and Few-Shot Image Classification

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第4期5卷 1658-1668页

作者： Zhang, Chunjie Zheng, Xiaolong Beijing Jiaotong University Institute of Information Science Beijing100044 China Beijing Jiaotong University Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China University of Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems The State of Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence Beijing100190 China

Most image classification methods are designed to either boost the classification accuracies with abundant supervision, or cope with the shortage of supervision information. This is often achieved by using the visual and semantic information of other sources. However, these methods use the visual and semantic information within the same class independently, leaving their intrinsic correlations unconsidered. Objects and disturbing components as well as noise exist on the same image. Besides, semantic representations also contain noisy information. To solve the problems mentioned above, we propose a novel method for both fully supervised image classification and few-shot image classification by decomposing visual and semantic correlations. We jointly explore the intrinsic correlations of visual and semantic information of images within the same class. For each class, we decompose its visual and semantic correlations using low-rank and sparse constraint respectively. The decomposed low-rank parts character the intrinsic correlations of images can be used in a linear transformation way. Using the decomposed parts of each class, Classification can be achieved by reconstruction error minimization. We conduct experiments on several datasets for both fully supervised image classification and few-shot image classification. Experimental results well show the effectiveness of the proposed method. © 2020 IEEE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Predicting microbe-disease associations via attention guided graph convolutional networks 4

Predicting microbe-disease associations via attention guided...

引用

4th International Conference on Biomedicine and Bioinformatics Engineering, ICBBE 2024

作者： Gong, Shiyun Zhu, Yuan School of Automation China University of Geosciences Lumo Road Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Lumo Road Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Lumo Road Hongshan District Hubei Wuhan430074 China School of Mathematics and Physics China University of Geosciences Lumo Road Wuhan430074 China

ISBN: (纸本)9781510682443

It is important to predict microbe-disease associations, as it helps to understand the cause of diseases episodes, the prevention of diseases, among other roles. Traditionally, the study of microbe-disease association is mainly based on laboratory purified culture for research and observation, which is highly scientific but has some limitations, such as some microbes needing to be cultured in a laboratory environment and costs heavily. This study proposes an attention guided graph convolutional network d approach (AGGCN) to predict possible potential associations between microbes and diseases. In the first place, AGGCN constructs four different similarity networks of microbes and diseases, which are combined with association networks to form a microbe-disease heterogeneous network. Subsequently, it is used as an input to the graph convolutional neural network to obtain each node embedding of this heterogeneous network. In this study, a three-layer network is used, so three different types of node embeddings can be obtained, and these three different types of node embedding representations are integrated via the multichannel graph attention mechanism to obtain the final node embeddings. Finally, the node embeddings obtained above are used for association prediction of microbes-diseases in heterogeneous networks. Experimentally verified, the AUC of AGGCN is 0.8972, and the AUPR is 0.5387. Comparative experimental results indicated that AGGCN shows better than the other five mainstream methods. It provides a new insight to explore network potential feature representation and predict associations between microbe and disease. © 2024 SPIE.

关键词： Graph neural networks

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：