检索结果-内蒙古大学图书馆

Representation learning via an integrated autoencoder for unsupervised domain adaptation

Frontiers of Computer Science 2023年第5期17卷 75-87页

作者： Yi ZHU Xindong WU Jipeng QIANG Yunhao YUAN Yun LI School of Information Engineering Yangzhou UniversityYangzhou 225127China Key Laboratory of Knowledge Engineering with Big Data(Ministry of Education of China) Hefei University of TechnologyHefei 230009China School of Computer Science and Information Engineering Hefei University of TechnologyHefei 230601China

The purpose of unsupervised domain adaptation is to use the knowledge of the source domain whose data distribution is different from that of the target domain for promoting the learning task in the target *** key bottleneck in unsupervised domain adaptation is how to obtain higher-level and more abstract feature representations between source and target domains which can bridge the chasm of domain ***,deep learning methods based on autoencoder have achieved sound performance in representation learning,and many dual or serial autoencoderbased methods take different characteristics of data into consideration for improving the effectiveness of unsupervised domain ***,most existing methods of autoencoders just serially connect the features generated by different autoencoders,which pose challenges for the discriminative representation learning and fail to find the real cross-domain *** address this problem,we propose a novel representation learning method based on an integrated autoencoders for unsupervised domain adaptation,called *** capture the inter-and inner-domain features of the raw data,two different autoencoders,which are the marginalized autoencoder with maximum mean discrepancy(mAE)and convolutional autoencoder(CAE)respectively,are proposed to learn different feature *** higher-level features are obtained by these two different autoencoders,a sparse autoencoder is introduced to compact these inter-and inner-domain *** addition,a whitening layer is embedded for features processed before the mAE to reduce redundant features inside a local *** results demonstrate the effectiveness of our proposed method compared with several state-of-the-art baseline methods.

关键词： unsupervised domain adaptation representation learning marginalized autoencoder convolutional autoen-coder sparse autoencoder

来源：评论

学校读者我要写书评

暂无评论

Joint Estimation of SOH and RUL for Lithium-Ion Batteries Based on Improved Twin Support Vector Machineh

引用

Energy engineering 2025年第1期122卷 243-264页

作者： Liyao Yang Hongyan Ma Yingda Zhang Wei He School of Electrical and Information Engineering Beijing University of Civil Engineering and ArchitectureBeijing100044China Institute of Distributed Energy Storage Safety Big Data Beijing100044China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing100044China

Accurately estimating the State of Health(SOH)and Remaining Useful Life(RUL)of lithium-ion batteries(LIBs)is crucial for the continuous and stable operation of battery management ***,due to the complex internal chemical systems of LIBs and the nonlinear degradation of their performance,direct measurement of SOH and RUL is *** address these issues,the Twin Support Vector Machine(TWSVM)method is proposed to predict SOH and ***,the constant current charging time of the lithium battery is extracted as a health indicator(HI),decomposed using Variational Modal Decomposition(VMD),and feature correlations are computed using Importance of Random Forest Features(RF)to maximize the extraction of critical factors influencing battery performance ***,to enhance the global search capability of the Convolution Optimization Algorithm(COA),improvements are made using Good Point Set theory and the Differential Evolution *** Improved Convolution Optimization Algorithm(ICOA)is employed to optimize TWSVM parameters for constructing SOH and RUL prediction ***,the proposed models are validated using NASA and CALCE lithium-ion battery *** results demonstrate that the proposed models achieve an RMSE not exceeding 0.007 and an MAPE not exceeding 0.0082 for SOH and RUL prediction,with a relative error in RUL prediction within the range of[-1.8%,2%].Compared to other models,the proposed model not only exhibits superior fitting capability but also demonstrates robust performance.

关键词： State of health remaining useful life variational modal decomposition random forest twin support vector machine convolutional optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Enhanced Privacy-Preserving WiFi Fingerprint Localization from CL Encryption

引用

Chinese Journal of Electronics 2024年第6期33卷 1435-1446页

作者： Zhiwei WANG Qiuchi ZHU Zhenqi ZHANG School of Computer Nanjing University of Posts and Telecommunications State Key Laboratory of Public Big Data Guizhou University Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu University of Information Engineering Key Laboratory of Computational Science and Application of Hainan Province Hainan Normal University

The WiFi fingerprint-based localization method is considered one of the most popular techniques for indoor localization. In INFOCOM'14, Li et al. proposed a wireless fidelity(WiFi) fingerprint localization system based on Paillier encryption, which is claimed to protect both client C 's location privacy and service provider S's database privacy. However, Yang et al. presented a practical data privacy attack in INFOCOM'18, which allows a polynomial time attacker to obtain S's database. We propose a novel WiFi fingerprint localization system based on CastagnosLaguillaumie(CL) encryption, which has a trustless setup and is efficient due to the excellent properties of CL encryption. To prevent Yang et al.'s attack, the system requires that S selects only the locations from its database that can receive the nonzero signals from all the available access points in C 's nonzero fingerprint in order to determine C's location. Security analysis shows that our scheme is secure under Li et al.'s threat model. Furthermore, to enhance the security level of privacy-preserving WiFi fingerprint localization scheme based on CL encryption, we propose a secure and efficient zero-knowledge proof protocol for the discrete logarithm relations in C's encrypted localization queries.

关键词： Location awareness Threat modeling data privacy Protocols databases Fingerprint recognition Trustless services Encryption Servers Wireless fidelity

来源：评论

学校读者我要写书评

暂无评论

Privacy Preserving Distributed Bandit Residual Feedback Online Optimization Over Time-Varying Unbalanced Graphs

引用

IEEE/CAA Journal of Automatica Sinica 2024年第11期11卷 2284-2297页

作者： Zhongyuan Zhao Zhiqiang Yang Luyao Jiang Ju Yang Quanbo Ge the School of Automation Nanjing University of Information Science and Technologyand also with Jiangsu Key Laboratory of Big Data Analysis Technology the School of Mechanical Engineering Shanghai Jiao Tong University IEEE

This paper considers the distributed online optimization(DOO) problem over time-varying unbalanced networks, where gradient information is explicitly unknown. To address this issue, a privacy-preserving distributed online one-point residual feedback(OPRF) optimization algorithm is proposed. This algorithm updates decision variables by leveraging one-point residual feedback to estimate the true gradient information. It can achieve the same performance as the two-point feedback scheme while only requiring a single function value query per iteration. Additionally, it effectively eliminates the effect of time-varying unbalanced graphs by dynamically constructing row stochastic matrices. Furthermore, compared to other distributed optimization algorithms that only consider explicitly unknown cost functions, this paper also addresses the issue of privacy information leakage of nodes. Theoretical analysis demonstrate that the method attains sublinear regret while protecting the privacy information of agents. Finally, numerical experiments on distributed collaborative localization problem and federated learning confirm the effectiveness of the algorithm.

关键词： Differential privacy distributed online optimization(DOO) federated learning one-point residual feedback(OPRF) time-varying unbalanced graphs

来源：评论

学校读者我要写书评

暂无评论

A survey of unmanned aerial vehicle flight data anomaly detection:Technologies,applications,and future directions

引用

Science China(Technological Sciences) 2023年第4期66卷 901-919页

作者： YANG Lei LI ShaoBo LI ChuanJiang ZHANG AnSi ZHANG XuDong School of Mechanical Engineering Guizhou UniversityGuiyang 550025China State Key Laboratory of Public Big Data Guizhou UniversityGuiyang 550025China

Flight data anomaly detection plays an imperative role in the safety and maintenance of unmanned aerial vehicles(UAVs).It has attracted extensive attention from ***,the problems related to the difficulty in obtaining abnormal data,low model accuracy,and high calculation cost have led to severe challenges with respect to its practical ***,in this study,firstly,several UAV flight data simulation softwares are presented based on a brief presentation of the basic concepts of anomalies,the contents of UAV flight data,and the public datasets for flight data anomaly ***,anomaly detection technologies for UAV flight data are comprehensively reviewed,including knowledge-based,model-based,and data-driven ***,UAV flight data anomaly detection applications are briefly described and ***,the future trends and directions of UAV flight data anomaly detection are summarized and prospected,which aims to provide references for the following research.

关键词： unmanned aerial vehicle(UAV) flight data anomaly detection data-driven

来源：评论

学校读者我要写书评

暂无评论

On Boolean elements and derivations in 2-dimension linguistic lattice implication algebras

引用

Applied Mathematics(A Journal of Chinese Universities) 2023年第2期38卷 274-292页

作者： ZHU Hua ZHAO Jian-bin School of Mathematics and Statistics Zhengzhou UniversityZhengzhou 450001China Henan Academy of Big Data Zhengzhou UniversityZhengzhou 450001China Henan Key Laboratory of Financial Engineering Zhengzhou 450001China Key Laboratory of Big Data Analysis and Application Zhengzhou 450001China

A 2-dimension linguistic lattice implication algebra(2DL-LIA)can build a bridge between logical algebra and 2-dimension fuzzy linguistic *** this paper,the notion of a Boolean element is proposed in a 2DL-LIA and some properties of Boolean elements are *** derivations on 2DL-LIAs are introduced and the related properties of derivations are ***,it proves that the derivations on 2DL-LIAs can be constructed by Boolean elements.

关键词： derivation Boolean element Lattice implication algebra(LIA) 2-dimension linguistic lattice implication algebra(2DL-LIA) 2-dimension fuzzy linguistic information

来源：评论

学校读者我要写书评

暂无评论

Unlocking high-efficiency oxygen evolution reaction through Co-N coordination engineering in Co@N-doped porous carbon core–shell nanoparticles

引用

Nano Research 2024年第8期17卷 7068-7076页

作者： Shucheng Liu Yu Shuai Xiaosi Qi Zhao Ding Yi Liu College of Big Data and Information Engineering Guizhou UniversityGuiyang 550025China College of Physics Guizhou Province Key Laboratory for Photoelectrics Technology and ApplicationGuizhou UniversityGuiyang 550025China

Modulation of metal sites coordination can significantly refine the electronic architecture of catalysts,thereby improving their catalytic *** work successfully developed a core–shell Co@N-doped porous carbon(Co@NC)catalyst by pyrolyzing the COF/MOF(IISERP-COF3/ZIF-67)composite in an inert *** Co@NC catalyst exhibited impressive oxygen evolution reaction(OER)performance,with a small overpotential of 304 mV and a modest Tafel slope of 88.6 mV·dec^(−1) in a 1 M KOH,alongside remarkable stability,maintaining 98.5%of its activity over 13 *** role of IISERP-COF3 was pivotal in preventing Co atom aggregation during the ZIF-67 pyrolysis,which facilitated the creation of mesopores for enhanced mass transport and ***,it effectively modulated the Co-N coordination to fine-tune the electronic structure,thereby optimizing the catalyst's capacity for adsorption of intermediates and boosting its intrinsic *** functional theory(DFT)studies corroborate that the exceptional OER efficiency of Co@NC can be linked to the enhanced Co-N coordination,optimizing the localized electronic structure at the Co active *** study not only proposes an innovative approach for optimizing COF/MOF as effective electrocatalysts but also clears the path for the emergence of affordable,high-performance alternatives to precious metal-based catalysts,marking a significant advancement in sustainable energy technologies.

关键词： covalent organic framework(COF) metal-organic framework(MOF) core-shell structure catalysts oxygen evolution reaction

来源：评论

学校读者我要写书评

暂无评论

Face micro-expression recognition algorithm based on ResNet depth model 8

Face micro-expression recognition algorithm based on ResNet ...

引用

8th International Conference on Intelligent Computing and Signal Processing, ICSP 2023

作者： Wang, Liquan Zhan, Shu Hefei University of Technology Key Laboratory of Big Data Knowledge Engineering Ministry of Education School of Computer and Information Engineering Hefei China

ISBN: (纸本)9798350302455

Micro Expression (ME) is the subtle facial expressions that people show when they express their inner feelings. To address the problem that micro-expression recognition is difficult and less accurate due to the small number of samples and uneven distribution of different categories, we propose a model framework to improve the accuracy of micro-expression recognition. The peak frames containing more key expression information in the micro-expression video sequences are extracted;SE-ResNeXt-50, an improved residual network with SE module, is used to extract features from the peak frames of micro-expressions, where the SE module can better learn the key information in the features, and ResNeXt simplifies the structure by replacing the dense structure with the sparse structure through group convolution, which improves the recognition efficiency. The recognition efficiency is improved by replacing the dense structure with the sparse structure by group convolution. At the same time, the Focal Loss loss function can better solve the model performance problem caused by the imbalance of micro-expression data. Simulation experiments are conducted on the micro-expression dataset CASME, and it is found that the improved residual network and peak frame improve the accuracy and F1 value of micro-expression recognition. The improved residual network and peak frame can reduce the effect of small data set, make the model have good fitting effect, and improve the performance of different categories, improve the recognition accuracy of micro-expressions, and have better recognition performance for micro-expression recognition. © 2023 IEEE.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Multi-Cluster Feature Selection Based on Isometric Mapping

引用

IEEE/CAA Journal of Automatica Sinica 2022年第3期9卷 570-572页

作者： Yadi Wang Zefeng Zhang Yinghao Lin Henan Key Laboratory of Big Data Analysis and Processing Henan UniversityKaifeng 475004 Institute of Data and Knowledge Engineering School of Computer and Information EngineeringHenan UniversityKaifeng 475004China

Dear editor,This letter presents an unsupervised feature selection method based on machine *** selection is an important component of artificial intelligence,machine learning,which can effectively solve the curse of d... 详细信息

关键词： problem letter dimensionality

来源：评论

学校读者我要写书评

暂无评论

An Evolutionary Multitasking Algorithm for Efficient Multiobjective Recommendations

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2025年第3期6卷 518-532页

作者： Tian, Ye Ji, Luke Hu, Yiwei Ma, Haiping Wu, Le Zhang, Xingyi Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Hefei230601 China Anhui University Institutes of Physical Science and Information Technology Hefei230601 China Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data Hefei230029 China

Represented by evolutionary algorithms and swarm intelligence algorithms, nature-inspired metaheuristics have been successfully applied to recommender systems and amply demonstrated effectiveness, in particular, for multiobjective recommendation. Owing to the population-based search paradigm, these algorithms can produce a number of recommendation lists, making diverse tradeoffs between multiple metrics and meeting the requirements of accuracy, novelty, diversity, and other user preferences. However, these algorithms are criticized for the low efficiency of the optimization process, especially when the number of users is large. To address this issue, this article proposes an evolutionary multitasking-based recommendation method, where each task corresponds to a user and all the tasks are optimized simultaneously, thus highly improving the efficiency of recommendation. To enhance the convergence speed, all the users are divided into multiple populations according to the similarity between their preferences, where each population evolves with internal knowledge transfer between users, and all the populations evolve with external knowledge transfer between populations. Experimental results on various datasets verify that the proposed method can better balance between multiple metrics than classical and deep neural network-based recommendation methods and exhibits significantly higher efficiency than evolutionary multiobjective optimization-based recommendation methods. © 2024 IEEE. All rights reserved.

关键词： Multiobjective optimization

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：