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

24,591 篇 会议
162 篇 期刊文献
57 册 图书
1 篇 学位论文
1 篇 科技报告

馆藏范围

24,812 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

10,147 篇 工学
- 6,341 篇 控制科学与工程
- 4,116 篇 计算机科学与技术...
- 2,664 篇 软件工程
- 2,149 篇 电气工程
- 1,866 篇 机械工程
- 1,146 篇 仪器科学与技术
- 738 篇 信息与通信工程
- 587 篇 生物工程
- 474 篇 生物医学工程（可授...
- 431 篇 光学工程
- 403 篇 力学（可授工学、理...
- 388 篇 电子科学与技术（可...
- 263 篇 化学工程与技术
- 252 篇 材料科学与工程（可...
- 252 篇 交通运输工程
- 244 篇 动力工程及工程热...
- 217 篇 土木工程
- 206 篇 建筑学
- 183 篇 安全科学与工程
3,076 篇 理学
- 1,767 篇 数学
- 906 篇 物理学
- 644 篇 生物学
- 581 篇 统计学（可授理学、...
- 482 篇 系统科学
- 229 篇 化学
1,226 篇 管理学
- 961 篇 管理科学与工程(可...
- 310 篇 工商管理
- 307 篇 图书情报与档案管...
328 篇 医学
- 287 篇 临床医学
- 205 篇 基础医学(可授医学...
122 篇 经济学
106 篇 法学
87 篇 农学
53 篇 教育学
27 篇 文学
16 篇 军事学
13 篇 艺术学
1 篇 哲学

主题

2,476 篇 predictive model...
1,994 篇 robots
1,827 篇 robotics and aut...
1,736 篇 computational mo...
1,714 篇 automation
1,650 篇 data models
1,584 篇 robot sensing sy...
1,489 篇 analytical model...
1,404 篇 adaptation model...
1,384 篇 training
1,175 篇 accuracy
1,141 篇 mathematical mod...
1,100 篇 trajectory
1,049 篇 mobile robots
916 篇 feature extracti...
843 篇 robustness
840 篇 robot kinematics
793 篇 control systems
718 篇 solid modeling
698 篇 uncertainty

机构

179 篇 university of ch...
144 篇 school of artifi...
111 篇 robotics institu...
88 篇 school of automa...
84 篇 institute of aut...
72 篇 shenyang institu...
69 篇 institutes for r...
68 篇 the robotics ins...
68 篇 school of electr...
64 篇 state key labora...
61 篇 school of mechat...
50 篇 department of au...
49 篇 department of au...
48 篇 state key labora...
46 篇 school of automa...
44 篇 school of mechan...
42 篇 robotics institu...
39 篇 school of automa...
32 篇 school of automa...
30 篇 college of autom...

作者

37 篇 secchi cristian
34 篇 yuechao wang
32 篇 yun-hui liu
31 篇 cristian secchi
29 篇 shugen ma
28 篇 lining sun
24 篇 xiang li
22 篇 jian wang
22 篇 jianda han
22 篇 fabio ramos
20 篇 xinyu wu
20 篇 wu xinyu
20 篇 daniela rus
19 篇 tomizuka masayos...
19 篇 wei li
19 篇 levine sergey
18 篇 c. laugier
18 篇 jie zhao
18 篇 chen chen
18 篇 dinesh manocha

语言

24,278 篇 英文
450 篇 其他
95 篇 中文
2 篇 西班牙文
1 篇 俄文

检索条件"任意字段=International Conference on Methods and Models in Automation and Robotics"

共 24812 条记录，以下是4091-4100 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：

Research on the Power Control of MMC-PET System Based on VSG and PBC 7

Research on the Power Control of MMC-PET System Based on VSG...

引用

7th IEEE international Electrical and Energy conference, CIEEC 2024

作者： Li, Huizhu Xia, Yan Chen, Yang Yang, Kai Sichuan University of Science & Engineering School of Automation and Information Engineering Yibin China

ISBN: (纸本)9798350359558

Power Electronic Transformer (PET) is a new type of power electronic device with flexible topology access, which has a wide range of application prospects in AC and DC microgrids. For the control of the MMC-PET system, which is cascaded by a modular multilevel converter (MMC) and dual active bridge (DAB), the traditional PI control method lacks damping inertia, has poor dynamic performance, and is unable to modulate the frequency actively. This paper proposes a current and voltage control technique based on virtual synchronous generators (VSG) theory and passivity-based control (PBC) theory. Firstly, the basic topology and working principle of MMC-PET are introduced, and the mathematical models of MMC and DAB are analyzed. Secondly, the passivity of MMC is investigated, and the passive controller is combined with the VSG control with primary FM to optimize the MMC-PET control so that the MMC-PET system has the function of primary FM with better robustness. Finally, the MMC-PET system model is constructed in Matlab/Simulink. The simulation experiments of the above VSG and PBC control methods are carried out under the working conditions of frequency fluctuation and load change in the power grid. The results show the feasibility and effectiveness of the proposed MMC-PET system model and control method. © 2024 IEEE.

关键词： Topology

来源：评论

学校读者我要写书评

暂无评论

Application of Predictive Algorithms in Informational Learning 2

Application of Predictive Algorithms in Informational Learni...

引用

2nd international conference on Data Analytics, Computing and Artificial Intelligence, ICDACAI 2023

作者： Han, Xue Hou, Guanyu Jilin Agricultural Science and Technology University Jilin Editorial Department of Journal Jilin China Harbin Institute of Technology School of Mechanical and Electrical Engineering and Automation Guangdong Shenzhen China

ISBN: (纸本)9798350339765

The application of predictive algorithms has penetrated into various fields, and their applications are becoming increasingly widespread in information learning. The popularization of online learning models and methods allows learners to utilize various and diverse learning resources, develop their knowledge and skills, and grow rapidly in learning. However, the rapid increase in learning resources and information has also brought huge challenges to learning, requiring more efficient learning methods. At this time, predictive algorithms have emerged. Predictive algorithms can analyze and evaluate learners' historical learning records and learning behavior patterns, predict learners' learning interests and needs, and recommend personalized learning resources. In this way, predictive algorithms provide efficient and accurate learning suggestions for students, helping to improve learning efficiency and outcomes. In the experimental data, 2.7% were very satisfied with the use of traditional information-based learning systems, and 98.2% were very satisfied with the use of deep learning prediction algorithms in information-based learning systems, indicating a significant improvement. Therefore, predictive algorithms have become an indispensable and important component in information learning. © 2023 IEEE.

关键词： Learning systems

来源：评论

学校读者我要写书评

暂无评论

Accelerated Life Test of Intelligent Harmonic Reducer for Robot

Accelerated Life Test of Intelligent Harmonic Reducer for Ro...

引用

Mechatronics and robotics Engineering (ICMRE), international conference on

作者： Shuo Zhang Bin He Fuze Xu Rui Yu Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai China

ISBN: (数字)9798350394276

ISBN: (纸本)9798350394283

In the life test experiment, accelerated life test significantly reduces the testing time and cost of robot harmonic reducer. In this paper, aiming at a robot intelligent harmonic reducer with electroplating temperature, noise and vibration sensors on the surface of flexwheel inner ring, an accelerated life test scheme of timed truncated robot intelligent harmonic reducer with constant stress loading is proposed. Torque speed and temperature are respectively used to represent the acceleration stress of harmonic reducer and sensor. This paper also designed the robot intelligent harmonic reducer acceleration life monitoring system and human-computer interaction interface, through the use of time domain feature analysis, frequency domain feature analysis and envelope demodulation analysis fault feature extraction methods to health harmonic reducer gear, wear and fracture fault harmonic reducer gear characteristic analysis, verify the feasibility of the system.

关键词： Temperature sensors Vibrations Torque Gears Life estimation Harmonic analysis Robot sensing systems

来源：评论

学校读者我要写书评

暂无评论

Guaranteed Gaussian Process Predictive Control for Lipschitz Nonlinear System with Input and State Constraints

Guaranteed Gaussian Process Predictive Control for Lipschitz...

引用

Mechatronics and robotics Engineering (ICMRE), international conference on

作者： Jinxin Zhang Hongze Wang Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Institute of Automation Chinese Academy of Sciences Beijing China

Though model predictive control can systematically handle the control problem of multi-input multi-output system under state and input constraints, it heavily depends upon the model of the controlled system. The non-parametric nature of the Gaussian Process endows it with the flexibility of modeling various practical systems and, more importantly, the ability to provide the level of confidence in its predictions, which makes it preferable to the model predictive control. Therefore, in this paper, these two approaches are combined into a whole scheme, called the Gaussian Process Predictive Control, which can make the system avoid some relatively uncertain areas, through incorporating the variance into the objective function. Then with some mild assumptions, the closed system stability and recursive feasibility is guaranteed theoretically, and validated by a standard simulation example.

关键词： Mechatronics Gaussian processes Predictive models Linear programming Control systems Stability analysis Nonlinear systems

来源：评论

学校读者我要写书评

暂无评论

IoT-Driven Mushroom Farm automation Using Neural Turing Machines (NTM) 4

IoT-Driven Mushroom Farm Automation Using Neural Turing Mach...

引用

4th IEEE international conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Manoj Kumar, S. Monica, C.L. Sunith Babu, L. Manikandan, V. Subramani, Dinesh Malik, Subhash Madanapalle Institute of Technology & Science Department of Mechanical Engineering Angallu India V.R.Siddhartha Engineering College Department of Environmental Science Vijayawada India M. S. Ramaiah Institute of Technology Department of Mechanical Engineering Bengaluru India Department of Computer Science and Engineering Bengaluru India Department of Artificial Intelligence and Data Science Erode India Maharishi Markendeshwar Engineering College Department of Mechanical Engineering Mullana India

ISBN: (纸本)9798350352931

Mushroom cultivation leads global agriculture due to its impact on worldwide trade. One of the main challenges in this area is optimal weather, especially temperature and humidity. Unfortunately, traditional farming's inability to achieve these conditions often leads to low yields. The recommended procedure involves collecting sensor data, constructing the model, and training it. Preprocessing includes spectral smoothing, normalization, and reflectance calibration. Sensors measure motion, temperature, light, and soil moisture. Photo feature extraction uses edge detection to identify objects. The model is trained using NTM. The suggested NTM-based model beats top-tier models like Random Forest (RF) and Support Vector Machine (SVM) with 92.35 percent accuracy. This increasing accuracy shows the model's mushroom production optimization. This proposed uses sensor data and current image processing techniques to improve mushroom farming conditions. NTM-based mushroom cultivation is more efficient and yields more than conventional methods. © 2024 IEEE.

关键词： Soil moisture

来源：评论

学校读者我要写书评

暂无评论

Power Quality Disturbances Classification Based on CNN Combining Knowledge Distillation and Incremental Learning 5

Power Quality Disturbances Classification Based on CNN Combi...

引用

5th international conference on Power Engineering, ICPE 2024

作者： Wu, Yiran Ren, Lintao Wang, Fei Hu, Jinglu Shanghai University School of Mechatronic Engineering and Automation Shanghai China Waseda University Graduate School of Information Production and Systems Fukuoka Japan

ISBN: (纸本)9798331531140

With the integration of renewable energy sources and new power electronic devices, power grid complexity has increased, leading to frequent power quality disturbances. Existing classification models often require retraining when dealing with new disturbance types, resulting in long update periods and significant use of computing resources. This paper proposes the FKDIL-CNN, a convolutional neural network model that combines knowledge distillation and incremental learning, enabling the enabling rapid adaptation to new disturbances without requiring full retraining. The FKDIL-CNN transfers identification knowledge for the known old types from a high-accuracy teacher model to the student model. By introducing a dynamic weight mechanism to improve the traditional knowledge distillation loss function, the student model efficiently distills old knowledge from the teacher model and performs incremental learning on new knowledge. Compared with the existing methods, our proposed FKDIL-CNN significantly reduces the training time and computing resource consumption while maintaining high classification accuracy. Additionally, this model demonstrates strong noise immunity, making it a practical solution for PQDs monitoring in complex power grid. © 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

automation of User Pace-Adjusted Treadmill: Comparison of Control methods based on LRF Sensors 46

Automation of User Pace-Adjusted Treadmill: Comparison of Co...

引用

46th Annual international conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Moreno, Brayan S. Mello, Ricardo C. Frizera, Anselmo Federal University of Espírito Santo Graduate Program in Electrical Engineering ES Vitória Brazil

ISBN: (纸本)9798350371499

Neurological disorders affect gait and posture, leading to significant difficulties in daily life. Traditional gait assessment lacks objective and quantifiable data, hindering comprehensive evaluation. To address these limitations, interactive and objective systems, such as smart walkers and specialized treadmills, have been developed utilizing advanced technologies to gather detailed gait data. This study focuses on evaluating two control strategies (A controller based on adaptive estimation of gait parameters and a PI controller-based systems) to automate a conventional treadmill, utilizing LRF sensors and the user's walking speed for personalized system control. The results demonstrate high adaptability of the control models to gait variations, surpassing reported walking speeds in the literature using these algorithms. These findings are relevant for enhancing user interaction and experience in rehabilitation applications and serious games, which can enable improvements in rehabilitation and human-machine interaction. Our results show that the strategy employing adaptive filters exhibits superior responsiveness, enabling adaptation to different treadmill speeds with greater ease. © 2024 IEEE.

关键词： Adaptive filtering

来源：评论

学校读者我要写书评

暂无评论

Point Cloud based Motion State Estimation Method for Autonomous Driving

Point Cloud based Motion State Estimation Method for Autonom...

引用

international conference on Advanced Mechatronic Systems (ICAMechS)

作者： Tao Jiang Enzhi Zhu Sidong Wu Linshuai Zhang Shuoxin Gu Lin Xu Qian Wang Xianggui Tang School of Intelligent Medicine Chengdu University of Traditional Chinese Medicine Unmanned System Intelligent Perception Control Technology Engineering Laboratory of Sichuan Province Chengdu University of Information Technology Chengdu School of Automation Chengdu University of Information Technology Chengdu School of Automation Chengdu University of Information Technology Unmanned System Intelligent Perception Control Technology Engineering Laboratory of Sichuan Province Chengdu University of Information Technology Chengdu School of Intelligent Medicine Chengdu University of Traditional Chinese Medicine School of Automation Chengdu University of Information Technology International Joint Research Center of Robotics and Intelligence System of Sichuan Province Chengdu School of Automation Chengdu University of Information Technology International Joint Research Center of Robotics and Intelligence System of Sichuan Province Chengdu School of Intelligent Medicine Chengdu University of Traditional Chinese Medicine Chengdu

Generally, motion vector information primarily stems from moving objects, while static objects contribute minimally to the estimation task. Traditional approaches for motion vector estimation typically rely on scene flow methods that depend on deep models to extract features from individual points at a high cost. These methods then acquire flow information through complex matching mechanisms or feature decoding. Such approaches are computationally expensive and exhibit substantial latency. Moreover, they neglect the importance of motion objects in motion vector estimation and the interference from static objects. Therefore, this paper introduces a novel method that first performs point cloud motion segmentation and subsequently estimates motion vectors. This approach focuses on leveraging point cloud information annotated with motion objects to estimate three-dimensional scene flow more effectively. By employing motion segmentation, we can obtain annotations for moving objects, enabling greater emphasis on the estimation of motion vectors for more challenging cases. In our experiments conducted on the KITTI dataset, the proposed method demonstrates superior performance compared to existing scene flow estimation methods. Specifically, without considering motion segmentation errors, the error in the motion direction is only 0.0363 m/s, showcasing better performance. Additionally, our method achieves an error of 0.076 m for three-dimensional endpoint error (EPE3D), showcasing distinct advantages over current scene flow networks.

关键词：

来源：评论

学校读者我要写书评

暂无评论

SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning

SERL: A Software Suite for Sample-Efficient Robotic Reinforc...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Jianlan Luo Zheyuan Hu Charles Xu You Liang Tan Jacob Berg Archit Sharma Stefan Schaal Chelsea Finn Abhishek Gupta Sergey Levine Department of EECS University of California Berkeley Department of Computer Science University of Washington Department of Computer Science Stanford University Intrinsic Innovation LLC

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In recent years, significant progress has been made in the field of robotic reinforcement learning (RL), enabling methods that handle complex image observations, train in the real world, and incorporate auxiliary data, such as demonstrations and prior experience. However, despite these advances, robotic RL remains hard to use. It is acknowledged among practitioners that the particular implementation details of these algorithms are often just as important (if not more so) for performance as the choice of algorithm. We posit that a significant challenge to the widespread adoption of robotic RL, as well as the further development of robotic RL methods, is the comparative inaccessibility of such methods. To address this challenge, we developed a carefully implemented library containing a sample efficient off-policy deep RL method, together with methods for computing rewards and resetting the environment, a high-quality controller for a widely adopted robot, and a number of challenging example tasks. We provide this library as a resource for the community, describe its design choices, and present experimental results. Perhaps surprisingly, we find that our implementation can achieve very efficient learning, acquiring policies for PCB board assembly, cable routing, and object relocation between 25 to 50 minutes of training per policy on average, improving over state-of-the-art results reported for similar tasks in the literature. These policies achieve perfect or near-perfect success rates, extreme robustness even under perturbations, and exhibit emergent recovery and correction behaviors. We hope these promising results and our high-quality open-source implementation will provide a tool for the robotics community to facilitate further developments in robotic RL. Our code, documentation, and videos can be found at https://***/

关键词： Training Perturbation methods Reinforcement learning Routing Libraries Software Robustness

来源：评论

学校读者我要写书评

暂无评论

Exploring Innovations in Autonomous robotics and Mechatronics: Application in Manufacturing and Healthcare

Exploring Innovations in Autonomous Robotics and Mechatronic...

引用

Smart Electronics and Communication (ICOSEC), international conference on

作者： T.Grace Shalini L. Ganeshabu Priyanka Chemudugunta Nagendar Yamsani Ch.Ashok Kumar A. Athiraja Department of Computational Intelligence School of Computing SRM Institute of Science and Technology (SRMIST)Kattankulathur Chengalpattu Tamil Nadu India Department of Robotics and Automation Rajalakshmi Engineering College Rajalakshmi Nagar Thandalam Mevalurkuppam Chennai Tamil Nadu India Department of Robotics and Automation Karpaga Vinayaga College of Engineering and Technology Chengalpattu Tamil Nadu India Department of School of Computer Science and Artificial Engineering SR University Warangal India Department of Mechanical Engineering Malla Reddy Engineering College Main Campus Maisammaguda Hyderabad Telangana India Department of CSE (AIML) Malla Reddy College of Engineering Secunderabad Telangana India

ISBN: (数字)9798331504403

ISBN: (纸本)9798331504410

Autonomous robotics and mechatronics have drastically changed the manufacturing and healthcare sectors by increasing productivity, precision, and flexibility. This work addresses the pressing need for new methods to advance these sectors by merging intelligent algorithms with autonomous systems. A hybrid strategy was employed, combining Deep Reinforcement Learning (DRL) and Adaptive Control Systems (ACS), to develop and optimize robotic operations. Extensive studies were conducted to assess the success of this strategy, which demonstrated a 25% reduction in operating expenses and a 30% increase in production efficiency in manufacturing settings. The method produced a precision rate of about 99% in the healthcare industry, which is significantly better than the 93% average of current systems. It also reduced patient recovery times by an estimated 20%. These results highlight the improved performance and promise of ACS with DRL combination in autonomous robotics, which may have revolutionary implications for the manufacturing and healthcare industries. The success, highlighted by economic and medical benefits, demonstrates the efficacy of our methodology and provides a strong platform for future developments in autonomous robotics and mechatronics.

关键词： Industries Technological innovation Mechatronics Service robots Scalability Medical services Manufacturing Adaptive control Tuning Testing

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500页 << < 406 407 408 409 410 411 412 413 414 415 > >>

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：