检索结果-内蒙古大学图书馆

2023 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2023

作者： Zhou, Linjie Gao, Wei Li, Ge Yuan, Hui Zhao, Tiesong Yue, Guanghui School of Electronic and Computer Engineering Peking University Shenzhen China School of Control Science and Engineering Shandong University Jinan China Fuzhou University Department of Communication Engineering Fuzhou China School of Biomedical Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9798350313154

Light field (LF) super-resolution has achieved remarkable results with the assumption of only downsampling. However, real-world LF scenes contain multiple degradation effects, which makes it difficult for existing methods to deal with hybrid distortions. In this paper, we propose a disentangled feature distillation framework for LF super-resolution with degradations. To reduce the learning difficulty, we propose a feature disentanglement mechanism to split the mixed reconstruction for both super-resolution and denoising into two single task learning processes. We also propose a feature enhancement strategy via knowledge distillation to transfer prior feature of each single reconstruction to our task of mixed reconstruction. Finally, the separate restored representations are fused to reconstruct a clean high-resolution LF. Experiments demonstrate the superior performance of our framework for different scale factors and noise levels. Additionally, our approach can also obtain excellent performance for joint super-resolution and deblurring, showing its gencralization for practical LF super-resolution applications. © 2023 IEEE.

关键词： Distillation

来源：评论

学校读者我要写书评

暂无评论

Fuzzy control design for time-delay systems under adaptive event-triggered mechanism

引用

Neural Computing and Applications 2024年第9期36卷 4727-4739页

作者： Du, Zhenbin Qu, Zifang Kao, Yonggui Wu, Zhaojing School of Computer and Control Engineering Yantai University Shandong Yantai264005 China School of Mathematics and Information Science Shandong Technology and Business University Shandong Yantai264005 China Department of Mathematics Harbin Institute of Technology Weihai264209 China School of Mathematics and Information Sciences Yantai University Shandong Yantai264005 China

This manuscript studies the fuzzy H∞ control design problem for nonlinear time-varying delay systems in fuzzy form via adaptive event-triggered mechanism. The fuzzy model and an adaptive event-triggered controller are connected in closed-loop form. A looped-functional is established to conduct stability analysis, and the main feature of this functional can fully reflect the sampling feature of control systems. Thus, the achieved results are less conservative. The Wringter inequality is also used to further relax stability analysis. Finally, sufficient conditions are achieved for the existence of event-triggered fuzzy controller, and the resulting closed-loop system reaches an H∞ control performance. Two examples verify the efficiency of the presented control strategy. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2023.

关键词： Time delay

来源：评论

学校读者我要写书评

暂无评论

Study on Impedance Coefficient Identification of Heating Pipe Network based on Reinforcement Learning Improved Differential Evolution 11

Study on Impedance Coefficient Identification of Heating Pip...

引用

11th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2023

作者： Zhao, Ming Guo, Zhengjun Li, Hui Liu, Yang Li, He School of Computer and Information Engineering Harbin University of Commence Harbin China Heilongjiang ZN Control Engineering Co. Ltd. Harbin China

ISBN: (纸本)9798350333664

With the improvement of process level and the development of intelligent technology, it becomes possible to obtain the operating parameters of the heating pipe network in real time, and the heating effect can be optimized by real-time analysis and adjustment of the operating parameters. However, this adjustment may affect the impedance coefficient of the heat supply pipe network. In this paper, an improved differential evolution algorithm based on reinforcement learning is proposed based on the hydraulic calculation model of the heating pipe network and applied to optimize the impedance coefficient. In addition, this paper also adopts a variety of other optimization algorithms, such as genetic algorithm, generalized inverse matrix method and differential evolution algorithm, respectively, to carry out the optimization identification of the model and conduct a comparative verification analysis. The results show that the optimized identification model proposed in this paper has high identification accuracy, can meet the process requirements of pipe network impedance parameter identification, and is suitable for the identification of complex pipe network impedance parameters. © 2023 IEEE.

关键词： differential evolution hydraulic modeling of heating network impedance parameter identification reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

controlling the Movement Path of Leg Exoskeletons Through Fractional Order Sliding Mode control 21

Controlling the Movement Path of Leg Exoskeletons Through Fr...

引用

21st International Multi-Conference on Systems, Signals and Devices, SSD 2024

作者： Znidi, Aicha Abdelhedi, Fatma Nouri, Ahmed Said Derbel, Nabil National Engineering School of Gabes University of Gabes Lab: Numerical Control of Industrial Processes Gabes6029 Tunisia Engineering College of Engineering King Abdulaziz: University Department of Electrical and Computer Jeddah22254 Saudi Arabia National Engineering School of Sfax University of Sfax Tunisia

ISBN: (纸本)9798350374131

This research introduces a new method, Fractional Order Sliding Mode control (FOSMC), to manage leg exoskele-tons during gait rehabilitation. This innovative algorithm utilizes fractional calculus principles to precisely regulate the joints of the exoskeleton. By integrating fractional order dynamics, the controller effectively handles the complexities and uncertainties inherent in human walking patterns. This leads to more precise tracking, lower energy usage, and increased comfort for patients during rehabilitation. Additionally, the application of Lyapunov theory ensures the stability of the system. The effectiveness of this control method is assessed through simulation examples in the study. © 2024 IEEE.

关键词： Sliding mode control

来源：评论

学校读者我要写书评

暂无评论

Research on fault diagnosis of geothermal heat pump based on EEMD and kmeans++ 7

Research on fault diagnosis of geothermal heat pump based on...

引用

7th IEEE Information Technology and Mechatronics engineering Conference, ITOEC 2023

作者： Zhao, Ming Guo, Zhengjun Liu, Yang Li, Hui Li, He Li, Yun Harbin University of Commence School of Computer and Information Engineering Harbin China Heilongjiang Zn Control Engineering Co. Ltd. Harbin China

ISBN: (纸本)9798350334197

With the development of technology and sustainable concept, ground source heat pump has gradually emerged in the heating industry, which is a new heating technology with the advantages of clean and high efficiency. However, with the continuous operation of the heat pump system, various faults may occur in the internal equipment of the system, such as evaporator fouling, compressor leakage, refrigerant line blockage, etc. It is of great practical significance to identify the fault types accurately and effectively. In this paper, the signal processing method adopts the ensemble empirical mode decomposition, which decomposes the collected ground source heat pump system signals, retains the relevant modal parameters and removes the residual terms, then evaluates each modal component using the approximate entropy as the feature evaluation index, and clusters the entropy values into feature vectors to determine the fault types. The experimental results show that the algorithm based on the combination of ensemble empirical mode decomposition and clustering can be applied to the fault diagnosis accuracy of ground source heat pump systems. © 2023 IEEE.

关键词： Empirical mode decomposition

来源：评论

学校读者我要写书评

暂无评论

Document-level Event Extraction combined with Writing Style and Argument Role RelationA Document-level Event Extraction model DEEWR 4

Document-level Event Extraction combined with Writing Style ...

引用

4th International Conference on Artificial Intelligence and computer engineering, ICAICE 2023

作者： Zhao, Jingsheng Yan, Shuai Ni, Qihui Wang, Yongzheng Zhu, Qiaoming School of Information and Control Engineering Qingdao University of Technology Qingdao266520 China School of Computer Science and Technology Soochow University Suzhou215006 China

ISBN: (纸本)9798400708831

Document-level event extraction is an important task in natural language processing, which faces the challenges of arguments-scattering and multi-events. The current mainstream method is to decompose document-level event extraction into three subtasks: entity extraction, event type recognition, and argument-filling. However, existing methods flew consider the impact of writing style on event extraction, and have complex models with high training costs. To address these problems, this paper proposes a document-level event extraction model that incorporates both writing style and argument role relation. First, Roberta is used to encode the document sentences to obtain semantic features, and BiLSTM-CRF is used to identify candidate entities. Second, the writing style is modeled as the relative distribution of argument roles in the document and is used to supervise the event type recognition results. Third, argument-filling is simplified to the relation judgment between the argument roles. This method effectively addresses the problem of scattered arguments by constructing event clusters based on the relation of argument roles. It also deals with the multi-event problem through event cluster division. Compared with previous path expansion-based methods, experimental results show that the model has lower training costs and performs better in low training epochs. © 2023 ACM.

关键词： Filling

来源：评论

学校读者我要写书评

暂无评论

Crysformer:An attention-based graph neural network for properties prediction of crystals

引用

Chinese Physics B 2023年第9期32卷 15-20页

作者：王田陈家辉滕婧史金钢曾新华 Hichem Snoussi Institute of Artificial Intelligence SKLSDEBeihang UniversityBeijing 100191China Zhongguancun Laboratory Beijing 100191China School of Aeronautic Science and Engineering Beihang UniversityBeijing 100191China School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China School of Software Engineering Xi'an Jiaotong UniversityXi'an 710049China Academy for Engineering and Technology Fudan UniversityShanghai 200433China Charles Delaunay Institute University of Technology of TroyesTroyes Cedex 10004France

We present a novel approach for the prediction of crystal material properties that is distinct from the computationally complex and expensive density functional theory(DFT)-based ***,we utilize an attention-based graph neural network that yields high-accuracy *** approach employs two attention mechanisms that allow for message passing on the crystal graphs,which in turn enable the model to selectively attend to pertinent atoms and their local environments,thereby improving *** conduct comprehensive experiments to validate our approach,which demonstrates that our method surpasses existing methods in terms of predictive *** results suggest that deep learning,particularly attention-based networks,holds significant promise for predicting crystal material properties,with implications for material discovery and the refined intelligent systems.

关键词： deep learning property prediction crystal attention networks

来源：评论

学校读者我要写书评

暂无评论

A blockchain based privacy-preserving federated learning scheme for Internet of Vehicles

引用

Digital Communications and Networks 2024年第1期10卷 126-134页

作者： Naiyu Wang Wenti Yang Xiaodong Wang Longfei Wu Zhitao Guan Xiaojiang Du Mohsen Guizani School of Control and Computer Engineering North China Electric Power UniversityChina Department of Mathematics&Computer Science Fayetteville State UniversityFayettevilleNCUSA Department of Electrical and Computer Engineering Stevens Institute of TechnologyHobokenNJ07030USA Department of Computer Science and Engineering Qatar UniversityDohaQatar

The application of artificial intelligence technology in Internet of Vehicles(lov)has attracted great research interests with the goal of enabling smart transportation and traffic ***,concerns have been raised over the security and privacy of the tons of traffic and vehicle *** this regard,Federated Learning(FL)with privacy protection features is considered a highly promising ***,in the FL process,the server side may take advantage of its dominant role in model aggregation to steal sensitive information of users,while the client side may also upload malicious data to compromise the training of the global *** existing privacy-preserving FL schemes in IoV fail to deal with threats from both of these two sides at the same *** this paper,we propose a Blockchain based Privacy-preserving Federated Learning scheme named BPFL,which uses blockchain as the underlying distributed framework of *** improve the Multi-Krum technology and combine it with the homomorphic encryption to achieve ciphertext-level model aggregation and model filtering,which can enable the verifiability of the local models while achieving ***,we develop a reputation-based incentive mechanism to encourage users in IoV to actively participate in the federated learning and to practice *** security analysis and performance evaluations are conducted to show that the proposed scheme can meet the security requirements and improve the performance of the FL model.

关键词： Federated learning Blockchain Privacy-preservation Homomorphic encryption Internetof vehicles

来源：评论

学校读者我要写书评

暂无评论

Green and Low Carbon Load Side Carbon Emission Measurement in Power Systems Based on Opportunity Constraints 11

Green and Low Carbon Load Side Carbon Emission Measurement i...

引用

11th China International Conference on Electricity Distribution, CICED 2024

作者： Xu, Zhiyuan Cheng, Liang School of Control and Computer Engineering North China Electric Power University Beijing China Institute of Software Chinese Academy of Sciences Tca Lab Beijing China

ISBN: (纸本)9798350368345

In the context of global warming, traditional carbon measurement methods have failed to completely capture the carbon emission dynamics of the power system under various operating states, resulting in biased carbon emission data. Moreover, there is still significant research space for measurement models on the power load side. To improve the accuracy and real-time performance of carbon emission measurement, this study designs a power system load side carbon emission measurement model based on opportunity constraints. The proposed model is built on opportunity constraints and fairness principles to allocate carbon emission responsibilities on the load side. On this basis, considering the dynamic characteristics of the power system, a two-stage carbon emission measurement model is raised, which uses dynamic carbon emission measurement method and node carbon potential method to calculate carbon emissions in the first and second stages, respectively. The outcomes validated that the carbon emissions of Unit 1 in the fixed carbon emission factor model were 620.07 tons, while they were reduced to 470.11 tons in the proposed model. After implementing demand response measures, the total carbon emissions of the system during peak electricity usage decreased by 3130 kg. The fixed carbon emission factor econometric model, traditional carbon market model, and the proposed model resulted in a total carbon emissions of 18306.61 tons, 16939.79 tons, and 19045.21 tons, respectively. Therefore, the proposed model performs better in regulating demand, can more accurately measure carbon emissions on the load side of the power system, and contribute to promoting green and low-carbon development of the energy system. © 2024 IEEE.

关键词： Low emission

来源：评论

学校读者我要写书评

暂无评论

An Attention-ReXNet Network for Long Tail Road Scene Classification 13

An Attention-ReXNet Network for Long Tail Road Scene Classif...

引用

13th IEEE International Conference on CYBER Technology in Automation, control, and Intelligent Systems, CYBER 2023

作者： Guo, Yuan H. Zhu, Jun R. Yang, Chang C. Yang, B. School of Computer Science and Artificial Intelligence Changzhou University Changzhou213000 China School of Microelectronics and Control Engineering Changzhou University Changzhou213000 China

ISBN: (纸本)9798350315196

With the development of assisted driving and autonomous driving, road scene classification has become increasingly important due to its ability to provide environmental information for drivers and autonomous driving, which is beneficial to reduce traffic accidents. However, road scene classification is limited by dataset imbalance and running speed, making it difficult to apply practically. To solve the problems mentioned above, we proposed an Attention-ReXNet network to conduct road scene classification. A balance Softmax cross-entropy is introduced to solve the class imbalance problem in road scene classification. The proposed method is evaluated in the Road Surface Classification Dataset (RSCD), which contains 27 categories and 1 million images with class imbalance. Experimental results show that Attention-ReXNet and balance Softmax cross entropy can achieve the best classification performance, with accuracy and top-1 being 87.67% and 88.52%, respectively. © 2023 IEEE.

关键词： Autonomous vehicles

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：