检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

350 篇 会议
104 篇 期刊文献
1 册 图书

馆藏范围

455 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

284 篇 工学
- 148 篇 计算机科学与技术...
- 133 篇 软件工程
- 112 篇 控制科学与工程
- 76 篇 机械工程
- 46 篇 电气工程
- 42 篇 信息与通信工程
- 38 篇 生物工程
- 33 篇 仪器科学与技术
- 31 篇 生物医学工程（可授...
- 25 篇 电子科学与技术（可...
- 18 篇 光学工程
- 15 篇 力学（可授工学、理...
- 15 篇 动力工程及工程热...
- 15 篇 化学工程与技术
- 13 篇 材料科学与工程（可...
- 12 篇 冶金工程
- 12 篇 建筑学
- 12 篇 土木工程
- 9 篇 石油与天然气工程
- 8 篇 交通运输工程
146 篇 理学
- 73 篇 数学
- 42 篇 物理学
- 39 篇 生物学
- 24 篇 统计学（可授理学、...
- 23 篇 系统科学
- 12 篇 化学
54 篇 管理学
- 43 篇 管理科学与工程(可...
- 20 篇 图书情报与档案管...
- 9 篇 工商管理
20 篇 医学
- 19 篇 临床医学
7 篇 法学
4 篇 经济学
4 篇 农学
3 篇 军事学

主题

16 篇 training
13 篇 feature extracti...
12 篇 accuracy
11 篇 internet of thin...
11 篇 data models
10 篇 simulation
10 篇 computational mo...
10 篇 predictive model...
9 篇 legged locomotio...
8 篇 reinforcement le...
8 篇 fuzzy systems
8 篇 control systems
8 篇 analytical model...
7 篇 deep learning
7 篇 force
7 篇 neural networks
7 篇 mobile robots
7 篇 robot sensing sy...
7 篇 real-time system...
6 篇 safety

机构

200 篇 institutes for r...
163 篇 key laboratory o...
121 篇 shenyang institu...
113 篇 university of ch...
87 篇 state key labora...
20 篇 chinese academy ...
18 篇 key laboratory o...
17 篇 school of electr...
17 篇 chinese academy ...
15 篇 school of artifi...
13 篇 school of inform...
11 篇 chinese academy ...
10 篇 college of infor...
10 篇 school of mechan...
10 篇 shenyang univers...
10 篇 department of me...
7 篇 shenzhen college...
7 篇 school of electr...
7 篇 college of autom...
7 篇 department of me...

作者

21 篇 peng zeng
20 篇 tao zhang
20 篇 song chunhe
18 篇 wu xinyu
16 篇 zeng peng
14 篇 zhang tao
13 篇 zhang hualiang
13 篇 chunhe song
12 篇 wang can
12 篇 hualiang zhang
11 篇 zhang yinlong
11 篇 wang zhongfeng
10 篇 liu yang
10 篇 yu shimao
9 篇 liang wei
9 篇 yang zhijia
8 篇 xinyu wu
8 篇 wei liang
7 篇 wang kai
7 篇 xi jin

语言

403 篇 英文
47 篇 其他
5 篇 中文

检索条件"机构=LABoratory of Intelligent Robotics Automation and Systems - LABIRAS"

共 455 条记录，以下是81-90 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Deep Learning-Based Prediction of Subsurface Oil Reservoir Pressure Using Spatio-Temporal Data 49

Deep Learning-Based Prediction of Subsurface Oil Reservoir P...

引用

49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Cheng, Haibo He, Yunpeng Zeng, Peng Li, Shichao Vyatkin, Valeriy Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Luleå University of Technology Department of Computer Science Electrical and Space Engineering Luleå Sweden Aalto University Department of Electrical Engineering and Automation Helsinki Finland

ISBN: (纸本)9798350331820

Prediction of subsurface oil reservoir pressure are critical to hydrocarbon production. However, the accurate pressure estimation faces great challenges due to the complexity and uncertainty of reservoir. The underground seepage flow and petrophysical parameters (permeability and porosity) are important but difficult to measure in oilfield. Deep learning methods have been successfully used in reservoir engineering and oil & gas production process. In this study, the effective but inaccessible subsurface seepage fields are not used, only the spatial coordinates and temporal information are selected as model input to predict reservoir pressure. A stacked GRU-based deep learning model is proposed to map the relationship between spatio-temporal data and reservoir pressure. The proposed deep learning method is verified by using a three-dimensional reservoir model, and compared with commonly-used methods. The results show that the stacked GRU model has a better performance and higher accuracy than other deep learning or machine learning methods in pressure prediction. © 2023 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Modeling of the Constant-Current Stimuli Response of a Bio-Robot for Long-Term Motion Control

Modeling of the Constant-Current Stimuli Response of a Bio-R...

引用

IEEE International Conference on robotics and Biomimetics

作者： Jie Zhou Yuan Fang Yang Chen Yao Li Bing Li Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Key University Laboratory of Mechanism & Machine Theory and Intelligent Unmanned Systems of Guangdong and with School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Bio-robots continue to receive attention because of their small size and low power consumption. Unfortunately, it currently faces two major obstacles before practical application. The first is the habituation issue, insects are difficult to be effectively controlled for a long time by electrical stimuli signals. The other one is the lack of model for motion control. In this research, we established a stimuli-response model for cockroach bio-robot based on long time current. A more convenient optic lobe implantation method has been proposed, which has lower attenuation and better stimuli effect. Constant electrical stimuli also significantly increased the number of effective controls for crawling. A cockroach bio-robot stimuli distance response model was established and validated with experiment data. Five parameters were including in this model, namely sex, length, weight, current amplitude and equivalent stiumated-number. This model can predict the movement distance of biological robots well.

关键词： Power demand Biological system modeling Insects Optical attenuators Predictive models Brain modeling Data models Motion control Robots Faces

来源：评论

学校读者我要写书评

暂无评论

Transmission Optimization Based on Industrial Internet Information Model 4

Transmission Optimization Based on Industrial Internet Infor...

引用

4th International Conference on Machine Learning and Computer Application, ICMLCA 2023

作者： Feng, Haiwen Tian, Hao Wang, Ting Zhu, Jingyang Wang, Xintong School of Software College Shenyang University of Technology Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798400709449

With the standardized development of industrial Internet, the communication among industrial Internet platforms, devices and gateways is more frequent. Due to the problems of heterogeneous data and low data interoperability existing in different devices, the communication between industrial Internet is hindered. With the development of industrial Internet information model, on the basis of reducing data heterogeneity and improving interoperability, it is more difficult to transmit information due to the increase of information content. Therefore, this paper will design an information model transmission optimization method, through the information model XML file content optimization compression, while in the information model may exist in the Chinese information processing, so that it can better compress the Chinese-English information. The results show that the XML file used in information transmission can be compressed by using this optimization method, and it is proved that the proposed optimization method can improve the transmission efficiency. © 2023 ACM.

关键词： Interoperability

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of OpenWSN Hardware Platform 2

Design and Implementation of OpenWSN Hardware Platform

引用

2nd International Conference on Algorithms, High Performance Computing and Artificial Intelligence, AHPCAI 2022

作者： Zhang, Shusheng Xie, Chuang Liu, Jun Zhao, Chun Yang, Zhijia Mao, Jizhi College of Automation and Electrical Engineering Shenyang Ligong University Shenyang110159 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9798350334784

This paper proposes a new wireless sensor network hardware platform based on OpenWSN project launched by the University of California, Berkeley. The hardware platform's processor uses a 32-bit microcontroller (STM32F103RCT6) produced by STMicroelectronics (ST), and the wireless module uses the WISA470 chip. The final experimental results show that this platform can support the Open WSN project very well. © 2022 IEEE.

关键词： Wireless sensor networks

来源：评论

学校读者我要写书评

暂无评论

Variation of sEMG with Muscle Fatigue for Lower Limb Stroke Patient During Walking

Variation of sEMG with Muscle Fatigue for Lower Limb Stroke ...

引用

2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Shang, Wenze Huang, Ruisen Liao, Wei-Hsin Wu, Xinyu Gao, Fei Southern University of Science and Technology Shenzhen518005 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen518055 China The Chinese University of Hong Kong Department of Mechanical and Automation Engineering Hong Kong999077 Hong Kong

ISBN: (纸本)9781665481090

SEMG signal is widely used and explored in control strategies of powered assistive human-robot interaction systems due to its non-invasive nature and ability to estimate motion intention well. However, prolonged use of the sEMG-based systems leads to muscle fatigue, contributing to unstable sEMG signals and regarding the performance of sEMG-based control strategies. In this study, three subjects, including two healthy subjects and one stroke subject, participated in our experiment, and the time domain, frequency domain, and complex features extracted from their sEMG signals were utilized to evaluate muscle fatigue. The results indicate that sEMG from the stroke side of the stroke subject contains more non-linear and chaotic parts, and the statistical differences between different trials are more significant, indicating that stroke has a more significant impact on the stroke side of the stroke subject. This study suggests that RMS in the stroke side of stroke subjects is less than that in others, whereas FuzzyEn in the stroke side of stroke subjects is greater than that in others, indicating that stroke leads to different motion patterns and more susceptibility to muscle fatigue. © 2024 IEEE.

关键词： Human robot interaction

来源：评论

学校读者我要写书评

暂无评论

Indoor Fingerprint Positioning Method Based on Real 5G Signals 23

Indoor Fingerprint Positioning Method Based on Real 5G Signa...

引用

7th International Conference on Machine Learning and Soft Computing, ICMLSC 2023

作者： Wang, Changhao Xi, Jin Xia, Changqing Xu, Chi Duan, Yong Shenyang University of Technology Shenyang110870 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9781450398633

Indoor positioning services are being used more and more widely. However, existing indoor positioning techniques cannot simultaneously take into account low cost, ease of use, high precision, and seamless switching between indoor and outdoor positioning. With the maturity of 5G techniques, 5G-based indoor positioning is gradually being paid attention to. 5G-based indoor positioning does not require additional equipment, and supports flexible indoor and outdoor switching under the same system. However, the 5G-related information used in existing research on 5G indoor positioning is not open to users. Therefore, in this paper, we propose an indoor fingerprint positioning method based on measured 5G signals. This method first collects 5G signals in the positioning area, and processes them to form a fingerprint database. Then, a machine learning algorithm is used to match the signal to be located with the fingerprint database to obtain the positioning result. Finally, we conduct experiments in real field, and the experimental result demonstrates that the positioning accuracy of our proposed method can reach 96%. © 2023 ACM.

关键词： 5G mobile communication systems

来源：评论

学校读者我要写书评

暂无评论

Feature Space Augmentation and Old Class Space Preservation for Class Incremental Learning

Feature Space Augmentation and Old Class Space Preservation ...

引用

第42届中国控制会议

作者： Ming Zeng Siying Li Jiazhe Liu Yuanhao Li Institute of Robotics and Automation Systems Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin University

The ability of continuously learning new knowledge without forgetting old ones is crucial to adapt to an ever-changing world. This scenario becomes more challenging when the previous data are not available. Current class incremental learning(CIL) approaches tend to incorporate new classes with backward compatibility, i.e., maintaining discriminability of old ones. By contrast, we focus on the extensibility and compatibility for future new classes in the early stage. Our proposed method achieves this by augmenting feature space. In detail, a large number of pseudo-new classes are generated via real example mixture and then train the initial spatially augmented model using pseudo-new classes and the base classes. Besides, considering the fact that it is impossible to maintain backward compatibility with only one prototype for each old class, the updated model also needs to preserve old class space in incremental stages. We employ a certain perturbation to the old class prototypes to effectively avoid old class space from being over-squeezed by the samples of new classes. The experiments on CIFAR-100 and ImageNet-Subset(100 classes) demonstrate that our method substantially reduces the overlap of old and new classes, outperforming state-of-the-art various baselines.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Design of a Mesh Crawling Robot with Beetle-Inspired Variable Stiffness Tarsus

Design of a Mesh Crawling Robot with Beetle-Inspired Variabl...

引用

IEEE International Conference on robotics and Biomimetics

作者： Hao Chen Kai Hu Longlong Hu Ziqi Zhou Yao Li Bing Li Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Key University Laboratory of Mechanism & Machine Theory and Intelligent Unmanned Systems of Guangdong Shenzhen China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Compared with large robots, micro-robots have the advantages of small size, low power consumption, and high concealment. For complex terrain, the crawling performance of micro-robots will be significantly reduced. In this study, the mesh surface was used as the crawling base of the robot, and a variable stiffness tarsus was designed with the beetle as a reference. This tarsus composed of multiple bending parts achieves a large range of stiffness changes, 0.07~0.495 N/mm. We have achieved stiffness control of the tarsus in a single actuation by trajectory planning of the claw ends. The proposed robot can achieve a big stiffness of the tarsus to resist the deformation of the tarsus due to external forces, which means that the robot can increase the adhesion ability when crawling at the stance phase. Therefore, even when the load was increased from 10g to 40g, the average crawling speed of the robot was not significantly reduced. This new tarsus can improve the crawling performance of the micro-robot on the mesh.

关键词： Legged locomotion Power demand Trajectory planning Force Kinematics Resists Bending Robots Substrates Trajectory optimization

来源：评论

学校读者我要写书评

暂无评论

Low-Power Heterogeneous Networking Method Based on NB-IoT and WSN 6

Low-Power Heterogeneous Networking Method Based on NB-IoT an...

引用

6th International Conference on Communication Engineering and Technology, ICCET 2023

作者： Guan, Mo Qi, Liangliang Jin, Xi Guan, Suoling Xia, Changqing Xu, Chi Shenyang University of Technology Shenyang110870 China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9798350336153

Digital oilfields generally adopt the multi-hop technology to expand the network scale, and the data generated depends on the large-scale wireless sensor network (WSN) for transmission. However, multi-hop communication will lead to uneven distribution of network energy consumption and premature death of nodes. To prolong the network lifetime of digital oilfields, we extended the narrowband internet of things (NB-IoT) module on some WSN nodes deployed on site to form heterogeneous nodes. Through the heterogeneity of NB-IoT and WSN, the nodes could transmit as little data as possible from other nodes, fundamentally reducing the node energy consumption. Furthermore, an optimization method was proposed that could simultaneously optimize the network lifetime and node expansion cost. The experimental results revealed that the proposed algorithm could greatly prolong the network lifetime while only introducing a small number of nodes. © 2023 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Prior Knowledge Informed Neural Network for Subsurface Flow Prediction

Prior Knowledge Informed Neural Network for Subsurface Flow ...

引用

IEEE International Symposium on Industrial Electronics (ISIE)

作者： Haibo Cheng Shichao Li Peng Zeng State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

Data-driven deep learning has been widely applied to solve subsurface flow problems. However, it is difficult to achieve accurate prediction with pure data-driven methods, especially when there is only a small amount of valid data. Prior knowledge is pre-existent and comes from an independent source. The neural network can be informed by prior knowledge to improve algorithm performance even with limited and sparse data. In this study, prior knowledge informed neural network (PKINN) is proposed to predict subsurface flow. The prior knowledge, on the one hand, is embedded in the neural networks as integrated loss function to inform the training process of deep learning methods. On the other hand, it is used as part of input term of neural network to improve calculation accuracy. Subsurface flow models are built to verify the proposed PKINN model. The results show that the PKINN method can solve subsurface flow problems effectively.

关键词： Knowledge engineering Deep learning Training Industrial electronics Solid modeling Accuracy Neural networks

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共46页 << < 5 6 7 8 9 10 11 12 13 14 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：