检索结果-内蒙古大学图书馆

22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Cheng, Ting Liang, Yonghui Xu, Qimin Zhu, Shanying Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 China

ISBN: (纸本)9798331527471

In industrial sites, multiple real-time control systems often share computing resources. However, burst computing tasks may lead to the random dropping of control computing subtasks, resulting in control failures and potential hazards. To address this issue, we propose an energy-efficient safety-aware task scheduling scheme based on mixed-integer programming. When burst computing tasks are triggered, this scheduling scheme adaptively releases resources from low-criticality control computing subtasks and adjusts the processor speed based on the dynamic voltage and frequency scaling technology (DVFS), ensuring the timely completion of burst computing tasks and keeping the control system state deviation within a safe threshold. To achieve the scheduling scheme, we propose an efficient algorithm called EESASA. Simulation results show that EESASA can minimize the overall cost of control and processor energy while ensuring the safety of the control system and the timely completion of burst computing tasks. © 2024 IEEE.

关键词： Dynamic frequency scaling

来源：评论

学校读者我要写书评

暂无评论

Attentive Neighborhood Feature Augmentation for Semi-supervised Learning

引用

Intelligent Automation & Soft Computing 2023年第8期37卷 1753-1771页

作者： Qi Liu Jing Li Xianmin Wang Wenpeng Zhao School of Computer Science and Cyber Engineering Guangzhou UniversityGuangzhou510002China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang UniversityFuzhou350121China

Recent state-of-the-art semi-supervised learning(SSL)methods usually use data augmentations as core *** methods,however,are limited to simple transformations such as the augmentations under the instance’s naive representations or the augmentations under the instance’s semantic *** tackle this problem,we offer a unique insight into data augmentations and propose a novel data-augmentation-based semi-supervised learning method,called Attentive Neighborhood Feature Aug-mentation(ANFA).The motivation of our method lies in the observation that the relationship between the given feature and its neighborhood may contribute to constructing more reliable transformations for the data,and further facilitating the classifier to distinguish the ambiguous features from the low-dense ***,we first project the labeled and unlabeled data points into an embedding space and then construct a neighbor graph that serves as a similarity measure based on the similar representations in the embedding ***,we employ an attention mechanism to transform the target features into augmented ones based on the neighbor ***,we formulate a novel semi-supervised loss by encouraging the predictions of the interpolations of augmented features to be consistent with the corresponding interpolations of the predictions of the target *** carried out exper-iments on SVHN and CIFAR-10 benchmark datasets and the experimental results demonstrate that our method outperforms the state-of-the-art methods when the number of labeled examples is limited.

关键词： Semi-supervised learning attention mechanism feature augmentation consistency regularization

来源：评论

学校读者我要写书评

暂无评论

A Secure Parameter Self-Tuning control Scheme for Vehicle Platoons under DoS Attacks 13

A Secure Parameter Self-Tuning Control Scheme for Vehicle Pl...

引用

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

作者： Han, Qiaoni Cheng, Guowen Tang, Zhenning Liu, Chang School of Electrical and Information Engineering Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System Tianjin University Tianjin300072 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Center for Biomedical Engineering School of Information Science and Technology Fudan University Shanghai200433 China

ISBN: (纸本)9798350315196

In order to mitigate the adverse impact of denial of service (DoS) attacks, this work designs a parameter self-tuning controller based on fuzzy rules for vehicle platoons with vehicle-to-vehicle (V2V) communications. Aiming at achieving the cooperative adaptive cruise control (CACC) of the vehicles with a required inter-vehicle distance and the same velocity, while considering the possible DoS attacks, we propose a parameter self-tuning longitudinal controller combining linear control and fuzzy control to enhance the stability and resilience of the platoon systems. Firstly, by analyzing the dynamic characteristics of vehicles and the mechanism of DoS attacks, we establish the dynamic model of vehicle platoons and model the impact of random DoS attacks as a constant data transmission delay, whose probability distribution can be defined using the Bernoulli random variable. Then, a linear controller based on fuzzy control is designed for longitudinal control to guarantee that the platoon keeps a reference velocity and the specified inter-vehicle distance under DoS attacks. Finally, thorough simulations are performed and the detailed results show the performance of the secure longitudinal control scheme for vehicle platoons in terms of stability and security. © 2023 IEEE.

关键词： Fuzzy control

来源：评论

学校读者我要写书评

暂无评论

Fast Super-Resolution DOA Estimation for Unknown Number of Radiation Sources Based on Complex Convolutional Neural Networks 2

Fast Super-Resolution DOA Estimation for Unknown Number of R...

引用

2nd IEEE International Conference on Signal, information and Data processing, ICSIDP 2024

作者： Ma, Hui Liu, Xianpeng Liu, Hongwei Yang, Junxiang Xidian University National Key Laboratory of Radar Signal Processing Xi'an China Xian Institute of Electromechanical Information Technology Electromechanical Dynamic Control Laboratory Xi'an China

ISBN: (纸本)9798331515669

To address the high computational complexity of traditional Direction of Arrival (DOA) estimation techniques and the limitations of previous neural networks in handling fixed signal sources, a new signal processing model was developed. This model employs sparse representation methods and deep learning through complex convolutional neural networks(CCNN). Focused research on the array's performance under unknown radiation sources using the complex convolutional neural network algorithm for super-resolution DOA estimation was conducted in a PyTorch environment. The results indicate that the complex convolutional model has a lower DOA computation complexity and higher precision in handling unknown radiation sources. After incorporating sparse representation with sampled data through the CCNN model for DOA estimation, an improvement in estimation accuracy and a reduction in computational complexity were observed compared to methods relying solely on sparse representation. Additionally, this model can effectively detect incoming waves from unknown radiation sources, unlike previous neural networks. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

A Novel Engine Safety State Assessment Model with Two-Layer Belief Rule Base Structure 11

A Novel Engine Safety State Assessment Model with Two-Layer ...

引用

11th IEEE International Conference on Behavioural and Social Computing, BESC 2024

作者： Miao, Shuo Deng, Qian Liu, Bingxin Lv, Yan Fang, Jiayue He, Wei Beijing institute of control and electronic technology Key Laboratory of Information System and Technology Beijing China Harbin Normal University Harbin China

ISBN: (纸本)9798331531904

Assessing the safety status of an engine is critical to the stable operation of electromechanical equipment. The belief rule base (BRB) model enables the integration of expert knowledge to assess the engine safety status, reduce the risk of accidents, and minimize major losses. However, when too many attributes are involved, the rapid growth in the number of rules not only increases the computational cost but also affects the model performance. For this reason, this study proposes a unique interval hierarchical BRB (IH-BRB) modeling approach for engine safety state assessment. The first layer utilizes the interval structure BRB as a classifier, effectively addressing the issue of exploding rule combinations. The second layer classifier employs multiple auxiliary BRBs to transform the multi-classification problem into a binary classification problem for each auxiliary BRB. This approach resolves the challenge of accurately evaluating interval BRB when data similarity is low. To complete the final safety state assessment, interpretability constraints are incorporated into the optimization process. This ensures that the optimized parameters align with expert knowledge and the actual situation. The efficacy of the model in engine safety state assessment is validated using the WD615 engine dataset. Comparison trials and experiments on other datasets further illustrate the advantages of the model in terms of assessment accuracy and interpretability. © 2024 IEEE.

关键词： Risk assessment

来源：评论

学校读者我要写书评

暂无评论

A Novel Coprime Nested Array with Enhanced DOFs and Reduced Mutual Coupling for DOA Estimation of Noncircular Sources

引用

IEEE Transactions on Vehicular Technology 2025年 1-13页

作者： Peng, Zhe Gong, Qishu Xie, Huikai School of Integrated Circuits and Electronics Beijing100081 China BIT Chongqing Institute of Microelectronics and Microsystems Chongqing401332 China Beijing Institute of Control and Electronics Technology Key Laboratory of Information System and Technology Beijing100038 China

Recently, many sparse array configurations have been designed for direction of arrival (DOA) estimation of noncircular sources due to their capability of constructing high-performance difference-sum coarray. Nested array, coprime array, along with their improved structures are the most commonly used array configurations. Nested arrays could provide O(R2) degrees of freedom (DOFs) with only R sensors, but suffer from severe mutual coupling effect owing to closely arranged elements. Coprime arrays generally offer a lower number of DOFs than nested arrays, but are more robust to mutual coupling effect due to sparser array structure. Unfortunately, existing sparse arrays cannot possess the benefits of nested arrays and coprime arrays at the same time within the framework of difference-sum coarray. To compensate for the above shortcoming, we first analyze the nesting property for difference coarray, and generalize the nesting property to difference-sum coarray, allowing nearly half of the sensors to be removed from dense subarray. Then, a new nested configuration called thinned coprime nested array (TCNA) is proposed, whose dense subarray is a coprime structure that satisfies the aforementioned nesting property. TCNA can generate a comparable number of DOFs to nested arrays due to the nesting property between two subarrays. Meanwhile, the mutual coupling effect is greatly reduced since its dense subarray is replaced with a coprime structure, which limits the number of sensor pairs with small spacing. Therefore, TCNA is able to combine the advantages of both nested array and coprime array. Finally, simulations verify the superiority of TCNA with respect to DOF ratio, coupling leakage, and DOA estimation accuracy. © 1967-2012 IEEE.

关键词： Direction of arrival

来源：评论

学校读者我要写书评

暂无评论

controllability of neighborhood Corona product networks

引用

Science China(information Sciences) 2024年第12期67卷 327-328页

作者： Bo LIU Xuan LI Qiang ZHANG Junjie HUANG Housheng SU Ministry of Education Key Laboratory for Intelligent Analysis and Security Governance of Ethnic Languages School of Information Engineering Minzu University of China School of Mathematical Sciences Inner Mongolia University Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology

controlling networks aims to study the models, structures,and related dynamics of complex networks. The primary problem of controlling networks is to determine whether they are controllable. Nowadays, controllability has been widely studied and applied to system engineering and control theory, power systems, aerospace, and quantum systems. Various classical criteria include the Gram matrix criterion, Kalman rank criterion, and PBH test.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Aerospace Relay Health Status Assessment Method Based on SMOTE-Enhanced EBRB 11

Aerospace Relay Health Status Assessment Method Based on SMO...

引用

11th IEEE International Conference on Behavioural and Social Computing, BESC 2024

作者： Fang, Jiayue Mai, Jiahao Lv, Yan Miao, Shuo He, Wei Beijing institute of control and electronic technology Key laboratory of information system and technology Beijing China Harbin Normal University Harbin China

ISBN: (纸本)9798331531904

The aerospace relay, a complex and precise power transmission system integrating electromagnetic and mechanical elements, holds vital significance for spacecraft safety, rendering its operational condition crucial. Therefore, it is imperative to conduct assessments of the health status of aerospace relays. However, existing models for aerospace relays are beset with issues related to data uncertainty and lack of interpretability of evaluation outcomes. Existing models for aerospace relays grapple with issues surrounding data uncertainty and the uninterpretable nature of their evaluation results. The extended belief rule base (EBRB) is a modeling approach adept at addressing uncertainties, characterized by a lucid inference mechanism and inherently interpretable results. However, current research has overlooked the fact that, during actual operation of aerospace relays, external disturbances and internal influences can lead to an imbalance among health status categories, resulting in a tendency for minority samples to be disregarded during training and rendering accurate evaluations of all categories unattainable. Consequently, this paper proposes an EBRB-based method for assessing the health status of aerospace relays that incorporates Synthetic Minority Over-sampling Technique (SMOTE). Firstly, the sample dataset is balanced using SMOTE. Secondly, an EBRB model is constructed to process the data. Lastly, ensemble reasoning (ER) algorithm is employed for fusion inference. In the experiment, the data processed by this model demonstrated obvious advantages across all performance indicators, indicating the model's powerful efficacy in the health status assessment of aerospace relays. © 2024 IEEE.

关键词： aerospace relay EBRB ER health status assessment SMOTE

来源：评论

学校读者我要写书评

暂无评论

Penetration-Free Collision Detection and Response Algorithm Based on Extended Position-Based Dynamics 6

Penetration-Free Collision Detection and Response Algorithm ...

引用

6th International Conference on Industrial Artificial Intelligence, IAI 2024

作者： Wang, Minghui Ding, Fan Liao, Chengye Pan, Yangyang Yang, Tao He, Jianping Pingtan Center of Quality Metrology and Testing Pingtan350400 China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Department of Automation Shanghai200240 China Northeastern University Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China

ISBN: (纸本)9798350356618

In the virtual simulation platform, frequent physical interactions between the robot and the environment poses extremely high demands on the handling of collisions and contacts in the simulation. Current mainstream virtual simulation platforms, in pursuit of real-time performance, have sacrificed some accuracy in simulation algorithms, leading to control strategies obtained in training that are difficult to directly transfer to actual physical machines. This virtual-physical discrepancy has significantly impacted the efficiency and effectiveness of mobile robot simulation. Existing work has attempted to use more accurate mathematical modeling and design more realistic solvers, but at the cost of uncontrollable problem scale and extremely high computational complexity. Starting from this perspective, this paper designs a non-penetration simulation algorithm based on extended Position-Based Dynamics (XPBD), which improves the physical processing accuracy during the simulation while ensuring real-time performance, enhances the fidelity of the simulation, and reduces the virtual-physical discrepancy. Simulation experiments have been conducted to validate the reliability of our proposed algorithm. © 2024 IEEE.

关键词： Virtual environments

来源：评论

学校读者我要写书评

暂无评论

STUDY ON COUPLING FAULT DIAGNOSIS OF THE PLANETARY TRANSMISSION GEARBOX BY USING WAVELET TRANSFORM AND 1DCNN 10

STUDY ON COUPLING FAULT DIAGNOSIS OF THE PLANETARY TRANSMISS...

引用

10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Qiu, Baolin Ma, Chao Wang, Shaohong Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology Beijing China Beijing Key Lab of Measurement and Control of Mechanical and Electrical System Beijing Information Science and Technology Beijing China

ISBN: (纸本)9781837242672

Considering the susceptibility of planetary transmission to strong noise interference, a fault diagnosis method is proposed based on Morlet wavelet transform and 1D Convolutional Neural Network (1DCNN). Firstly, the acceleration captured from the transmission is dealt with angle resampling to reduce the dependence of speed on signal characteristics, and band-pass filtering is performed, which parameter is determined by using the fast spectral kurtosis algorithm. Subsequently, the filtered data is decomposed into several multiple intrinsic mode function (IMF) components with the EEMD algorithm and reconstructed according to the correlation coefficient parameter. Then reconstructed data is subjected to further noise reduction processing using wavelet transform and the amplitude in the scale parameter with the highest kurtosis as the input to 1DCNN for training and fault diagnosis classification. The experimental results show that the proposed method can effectively reduce noise interference, the fault diagnosis accuracy of the processed data is relatively high. The fault diagnosis accuracy of the processed data is significantly higher than that of the raw data. © The Institution of Engineering & Technology 2024.

关键词： Noise abatement

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：