检索结果-内蒙古大学图书馆

2021 International Conference on Computer Application and Information Security, ICCAIS 2021

作者： Ji, Zhongchang Zhu, Wenxing School of Control Science and Engineering Shandong University Jinan China

ISBN: (纸本)9781510655218

This paper proposes a method to fill in the missing traffic data by using multi-source data. Due to the regularity and specificity of traffic data, Gru network is used to capture missing patterns. The processed missing data, mask data and time interval data are input into Gru network for more in-depth information capture. The results of road speed matching for the floating vehicle data on the road in the corresponding period are further studied by Gru network, and the two results are fused to obtain the filling value of missing value. © The Authors.

关键词： Recurrent neural networks

来源：评论

学校读者我要写书评

暂无评论

Human-Robot Interaction control Based on the RBF Neural Network for Upper Limb Rehabilitation Robot 7

Human-Robot Interaction Control Based on the RBF Neural Netw...

引用

7th Asian Conference on Artificial Intelligence Technology, ACAIT 2023

作者： Tian, Zhenda Liu, Keping Liu, Yongbai Wang, Gang Shen, Yao Sun, Zhongbo Changchun University of Technology Department of Control Science And Engineering Changchun China Changchun University of Technology Mechanical Engineering Changchun China Changchun University of Technology School of Electrical And Information Engineering Jilin Engineering Normal University Department of Control Science And Engineering Changchun China

ISBN: (纸本)9798350359145

Radical basis function (RBF) neural network is proposed for the upper limb rehabilitation robot driven by series elastic actuator (SEA). The human-in-charge (HIC) mode and the robot-in-charge (RIC) mode are performed via the devised interaction control algorithm, where in the different control modes can be switched smoothly to avoid human-robot confrontation and improve the rehabilitation effect. On the basis of the RBF neural network with nonlinear mapping property, the human-robot interaction control modes can be dynamically adjusted via utilizing human-robot interaction force, which realizes the human-robot collaboration and adaptive control. The simulation results prove that the advised control method has a excellent performance different control modes. © 2023 IEEE.

关键词： Human robot interaction

来源：评论

学校读者我要写书评

暂无评论

Optimal Isobath Routing Strategy based on Multibeam Bathymetry Technology 2

Optimal Isobath Routing Strategy based on Multibeam Bathymet...

引用

2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Chen, Jieyu Liu, Yansha Luo, Ao Liu, Xiaodong Kong, Siyi Xu, Yuxiang Nanjing University of Technology School of Electrical Engineering and Control Science Nanjing China Xuzhou Construction Engineering Testing Center Co. Ltd Xuzhou China

ISBN: (纸本)9798350317558

With the rapid development of channel survey technology, multibeam bathymetric system plays an increasingly important role in channel survey. Firstly, we establish a physical model, use the tangent formula to find out the depth of seawater D, after the analysis of the plane model and use the sine theorem to find out the coverage width W, and then use the spacing of the two adjacent survey lines and the coverage width, and with the help of the expression of the relationship between the overlap rate with the previous survey line is solved ?. The overlap with the previous line is then solved with the help of an expression relation. Finally, SketchUp was used to convert the given information into a three-dimensional model for analysis, and the expression for the relationship between angles and edges in a three-dimensional structure was obtained. We found that the optimal wiring strategy is "horizontal wiring along the isobaths", and the optimal number of survey lines for the vessel on these three slopes is 67 in total, with the missed area accounting for 1.325% of the total area of the region. © 2024 IEEE.

关键词： Channel Survey multibeam bathymetric optimal wiring strategy plane model survey lines

来源：评论

学校读者我要写书评

暂无评论

Deep Reinforcement Learning-based Computing Offloading and Resource Allocation Algorithm in Internet of Vehicles 11

Deep Reinforcement Learning-based Computing Offloading and R...

引用

2023 IEEE 11th International Conference on Information, Communication and Networks, ICICN 2023

作者： Yuan, Yiping Chen, Xin Jiao, Libo Wang, Yijie Beijing Information Science & Technology University School of Control Science and Engineering Beijing China Beijing Information Science & Technology University School of Computer Science Beijing China

ISBN: (纸本)9798350314014

With the rapid emergence of the Internet of Vehicles (IoV) and 6G networks, the exponential growth in data traffic has presented a formidable challenge to the limited computational capabilities of in-vehicle devices. To overcome this challenge, mobile edge computing (MEC) offers a viable solution by offloading computationally intensive tasks to the edge servers. In this study, we design a novel joint optimization approach that leverages deep reinforcement learning (DRL) to inform decisions on computational offloading, energy consumption, and resource allocation. Our proposed scheme considers the involvement of both the base station (BS) and road side units (RSUs) in providing computing resources to the user while simultaneously minimizing energy consumption and reducing latency of computational tasks. Our simulations unequivocally establish the efficacy of the Deep Reinforcement Learning-based computing offloading and resource allocation (DCORA) algorithm. The proposed DCORA algorithm outperforms alternative baseline schemes by approximately 15% in direct comparison. © 2023 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Connection Fault Diagnosis for Series-connected Lithium-ion Battery Based on Curve Similarity Calculation and Curve Conversion 6

Connection Fault Diagnosis for Series-connected Lithium-ion ...

引用

6th CAA International Conference on Vehicular control and Intelligence, CVCI 2022

作者： Ding, Xinchao Cui, Zhongrui Cui, Naxin School of Control Science and Engineering Shandong University Jinan China

ISBN: (数字)9781665453745

ISBN: (纸本)9781665453745

In electric vehicles (EVs), the connection faults in lithium-ion battery packs may cause accelerated battery aging and inconsistency. Timely and effective connection fault diagnosis is of great significance to ensure the safe operation of EVs. This paper proposes a connection fault diagnosis method for series-connected battery packs based on the combination of edit distance on real-sequence (EDR) and charging capacity-voltage (QV) curve conversion. The method can determine the location of the faulty cell and the preliminary quantification of fault degree by calculating the similarity of the cell charging curve. Then, by calculating the conversion parameters, the specific connection resistance value can be calculated and distinguished from the internal resistance. A set of experiments were designed on series-connected batteries to simulate the connection faults with different severity. The experimental results show that the method can effectively locate the connection fault and diagnose its severity in the series-connected batteries without complex battery model. © 2022 IEEE.

关键词： Lithium-ion batteries

来源：评论

学校读者我要写书评

暂无评论

Predictive control Strategy for Four-switch Buck-Boost Converter with Mode Smooth Transition 6

Predictive Control Strategy for Four-switch Buck-Boost Conve...

引用

6th CAA International Conference on Vehicular control and Intelligence, CVCI 2022

作者： Cao, Entong Ding, Wenlong Duan, Bin Song, Jinqiu Zhan, Chenzhong Wan, Dongxiang Zhang, Chenghui School of Control Science and Engineering Shandong University Jinan China

ISBN: (数字)9781665453745

ISBN: (纸本)9781665453745

Four-switch buck-boost converter (FSBB) has received extensive attention in the fields of power battery test and energy storage because of its bidirectional buck and boost capabilities, which are suitable for wide-range voltage changes. However, due to its complex mode detection and disturbance brought by mode transition, it faces great challenge of operating mode selection and also has difficulty in achieving smooth mode transition. In this paper, a mode selection and transition strategy based on predictive control strategy is proposed, and the traditional three modes of FSBB are expanded to four modes, which reduces the sudden change of duty cycle resulted from control dead zones. The predictive control method is used to select the best working mode and ensure smooth transition of working mode. The simulation results demonstrate that the proposed method can successfully accomplish the aforementioned functions and exhibit strong dynamic performance when the input voltage and output are almost equal. © 2022 IEEE.

关键词： Buck-Boost converter

来源：评论

学校读者我要写书评

暂无评论

Object Detection Methods for Autonomous Driving in Adverse Weather Conditions 3

Object Detection Methods for Autonomous Driving in Adverse W...

引用

3rd International Conference on Electronics and Information Technology, EIT 2024

作者： Wang, Yuantao Lu, Yuanyao Qiu, Yongsheng Yang, Chaochao North China University of Technology School of Electrical and Control Engineering Beijing China North China University of Technology School of Information Science and Technology Beijing China

ISBN: (纸本)9798350369151

Autonomous driving systems open up a new frontier in the automotive industry, offering new possibilities for future transportation with increased efficiency and a comfortable experience. However, object detection in adverse weather conditions remains a challenge that hinders the advancement of higher-level autonomous driving. This paper provides a detailed report on the latest developments in target detection algorithms under adverse weather conditions. It analyzes the impact of adverse weather on autonomous vehicle sensors, the establishment and use of related datasets, research on image restoration algorithms for adverse weather conditions and their effects on target detection tasks, and the application of domain adaptation methods in transfer learning for target detection. Additionally, the paper discusses future work and potential research areas in this field. © 2024 IEEE.

关键词： Automotive industry

来源：评论

学校读者我要写书评

暂无评论

DOUBLE WAVELET THRESHOLD FILTER DESIGN FOR REAL-TIME ADAPTIVE DENOISING IN OA-ICOS

DOUBLE WAVELET THRESHOLD FILTER DESIGN FOR REAL-TIME ADAPTIV...

引用

2024 Jiangsu Annual Conference on Automation, JACA 2024

作者： Deng, Yixin Wang, Zairan Chen, Yang-Yang Liu, Qin Wang, Xiangyu School of Automation Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China School of Cyber Science and Engineering Southeast University Nanjing China

ISBN: (纸本)9781837242689

In the Off-Axis Integrated Cavity Output Spectroscopy (OA-ICOS) technique, single-stage filters are commonly used to reduce noise and improve the signal-to-noise ratio, enabling more precise CO2 concentration detection. However, these filters often underperform under real-time conditions. To enhance real-time performance, this paper proposes a novel framework based on Double Wavelet Threshold Filter (DWTF) that adaptively suppresses noise while preserving key features of CO2 concentration signal. Firstly, one wavelet threshold filter (WT) is introduced to calculate the mean of the current sequence, providing an initial denoising step. Secondly, another WT is employed to extract features from a longer sequence for adaptive computation of the discount factor. Finally, an exponential moving average filter (EMA) is applied to combine both current and historical data to produce a smoother aggregated output. To validate the effectiveness, DWTF was compared with other conventional algorithms for a CO2 dataset with three distinct states: smooth, ship and mutant, obtained by OA-ICOS. The experimental results demonstrate that DWTF performs effectively in all three states. © The Institution of engineering & Technology 2024.

关键词： Adaptive filters

来源：评论

学校读者我要写书评

暂无评论

Slow Convergence of Interacting Kalman Filters in Word-of-Mouth Social Learning 60

Slow Convergence of Interacting Kalman Filters in Word-of-Mo...

引用

60th Annual Allerton Conference on Communication, control, and Computing, Allerton 2024

作者： Krishnamurthy, Vikram Rojas, Cristian R. School of Electrical and Computer Engineering Cornell University United States School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Division of Decision and Control Systems Stockholm Sweden

ISBN: (纸本)9798331541033

We consider word-of-mouth social learning involving m Kalman filter agents that operate sequentially. The first Kalman filter receives the raw observations, while each subsequent Kalman filter receives a noisy measurement of the conditional mean of the previous Kalman filter. The prior is updated by the m-th Kalman filter. When m=2, and the observations are noisy measurements of a Gaussian random variable, the covariance goes to zero as k-1/3 for 7kappa;observations, instead of O(k-1) in the standard Kalman filter. In this paper we prove that for m agents, the covariance decreases to zero as k-(2m-1), i.e, the learning slows down exponentially with the number of agents. We also show that by artificially weighing the prior at each time, the learning rate can be made optimal as k-1. The implication is that in word-of-mouth social learning, artificially re-weighing the prior can yield the optimal learning rate. © 2024 IEEE.

关键词： Kalman filters

来源：评论

学校读者我要写书评

暂无评论

Synergistic cytotoxicity of binary combinations of inorganic and organic disinfection byproducts assessed by real-time cell analysis

引用

Journal of Environmental sciences 2022年第7期34卷 222-231页

作者： Mengge Fan Longfei Shu Xinran Zhang Miao Yu Yongting Du Junlang Qiu Xin Yang Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology School of Environmental Science and EngineeringSun Yat-sen UniversityGuangzhou 510006China

Chlorine, chlorine dioxide, and ozone are widely used as disinfectants in drinking water treatments. However, the combined use of different disinfectants can result in the formation of various organic and inorganic disinfection byproducts(DBPs). The toxic interactions, including synergism, addition, and antagonism, among the complex DBPs are still unclear. In this study, we established and verified a real-time cell analysis(RTCA) method for cytotoxicity measurement on Chinese hamster ovary(CHO) cell. Using this convenient and accurate method, we assessed the cytotoxicity of a series of binary combinations consisting of one of the 3 inorganic DBPs(chlorite, chlorate, and bromate) and one of the 32 regulated and emerging organic DBPs. The combination index(CI) of each combination was calculated and evaluated by isobolographic analysis to reflect the toxic interactions. The results confirmed the synergistic effect on cytotoxicity in the binary combinations consisting of chlorite and one of the 5 organic DBPs(2 iodinated DBPs(I-DBPs) and 3 brominated DBPs(Br-DBPs)), chlorate and one of the 4 organic DBPs(3 aromatic DBPs and dibromoacetonitrile), and bromate and one of the 3 organic DBPs(2 I-DBPs and dibromoacetic acid). The possible synergism mechanism of organic DBPs on the inorganic ones may be attributed to the influence of organic DBPs on cell membrane and cell antioxidant system. This study revealed the toxic interactions among organic and inorganic DBPs, and emphasized the latent adverse outcomes in the combined use of different disinfectants.

关键词： Disinfection byproducts(DBPs) Real-time cell analysis(RTCA) Synergistic cytotoxicity

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：