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

381 篇 会议
136 篇 期刊文献
1 册 图书

馆藏范围

518 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

320 篇 工学
- 148 篇 计算机科学与技术...
- 138 篇 软件工程
- 134 篇 控制科学与工程
- 78 篇 机械工程
- 65 篇 电气工程
- 45 篇 仪器科学与技术
- 45 篇 信息与通信工程
- 34 篇 电子科学与技术（可...
- 31 篇 生物工程
- 20 篇 化学工程与技术
- 19 篇 材料科学与工程（可...
- 18 篇 冶金工程
- 16 篇 光学工程
- 14 篇 力学（可授工学、理...
- 14 篇 交通运输工程
- 14 篇 生物医学工程（可授...
- 14 篇 安全科学与工程
- 13 篇 动力工程及工程热...
- 12 篇 建筑学
- 12 篇 土木工程
147 篇 理学
- 78 篇 数学
- 45 篇 物理学
- 28 篇 生物学
- 27 篇 系统科学
- 24 篇 统计学（可授理学、...
- 14 篇 化学
62 篇 管理学
- 53 篇 管理科学与工程(可...
- 17 篇 图书情报与档案管...
- 11 篇 工商管理
10 篇 医学
8 篇 经济学
7 篇 法学
3 篇 农学
3 篇 军事学

主题

21 篇 control systems
15 篇 robot kinematics
14 篇 training
13 篇 robot sensing sy...
13 篇 feature extracti...
11 篇 internet of thin...
11 篇 manipulators
11 篇 accuracy
10 篇 legged locomotio...
10 篇 force
10 篇 robots
10 篇 trajectory
10 篇 mathematical mod...
10 篇 data models
9 篇 computational mo...
9 篇 predictive model...
9 篇 robustness
8 篇 reinforcement le...
8 篇 deep learning
8 篇 safety

机构

183 篇 institutes for r...
164 篇 key laboratory o...
121 篇 shenyang institu...
88 篇 university of ch...
64 篇 state key labora...
20 篇 chinese academy ...
19 篇 key laboratory o...
18 篇 school of electr...
18 篇 chinese academy ...
14 篇 school of artifi...
13 篇 school of inform...
11 篇 chinese academy ...
10 篇 college of infor...
10 篇 shenyang univers...
9 篇 state key labora...
9 篇 institute of rob...
7 篇 school of electr...
7 篇 college of autom...
7 篇 research institu...
6 篇 hubei key labora...

作者

25 篇 stjepan bogdan
21 篇 tao zhang
21 篇 peng zeng
20 篇 song chunhe
16 篇 zeng peng
14 篇 zhang tao
14 篇 qiang huang
13 篇 matko orsag
13 篇 zhang hualiang
13 篇 bogdan stjepan
13 篇 hualiang zhang
13 篇 chunhe song
11 篇 zhang yinlong
11 篇 wang zhongfeng
10 篇 liu yang
10 篇 yang zhijia
10 篇 yu shimao
9 篇 liang wei
8 篇 haibin yu
8 篇 wei liang

语言

500 篇 英文
12 篇 其他
6 篇 中文

检索条件"机构=Laboratory for Robotics and Intelligent Control Systems - LARICS"

共 518 条记录，以下是331-340 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：

A Fast-trained and Generalized Spiking Neural Network for Robotic Gas Source Localization

A Fast-trained and Generalized Spiking Neural Network for Ro...

引用

International Conference on Advanced robotics and Mechatronics (ICARM)

作者： Chiyang Liu Xinxing Chen Jian Huang Hubei Key Laboratory of Brain-inspired Intelligent Systems and the Key Laboratory for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

Mobile robots for Gas Source Localization (GSL) tasks are a safer alternative than human and animal rescuers in hazardous scenarios. Existing research primarily concentrates on rule-based algorithms or conventional artificial neural networks (ANNs). However, these approaches are either inapplicable in cluttered environments or undeployable due to their high energy consumption and the demand for substantial computational resources. This paper introduces the application of energy-efficient spiking neural networks (SNNs) to address robotic GSL tasks. A pipeline is proposed to train SNNs with deep Q learning and a pretrain-finetune paradigm. To facilitate the training process, a small dataset of gas dispersion is generated utilizing openFoam and GADEN, a high-fidelity simulator for gas dispersion. Data from a simplified plume model are leveraged to pretrain an ANN, the activation function of which gradually transitions from a bounded rectified linear unit (bReLU) to a step function. Subsequently, an SNN initialized with the ANN parameters undergoes finetuning on the GADEN-based dataset. The training pipeline significantly reduces training time compared to direct training of SNNs. The trained SNN is validated within the GADEN simulation environment and compared to three different models, demonstrating promising performance and superior generalization despite limited training data.

关键词： Training Location awareness Q-learning Mechatronics Pipelines Training data Spiking neural networks Data models Mobile robots Dispersion

来源：评论

学校读者我要写书评

暂无评论

An Abnormal State Forecasting Method for Substation Equipment based on Improved LSTM

An Abnormal State Forecasting Method for Substation Equipmen...

引用

2019 IEEE Sustainable Power and Energy Conference, iSPEC 2019

作者： Li, Tong Yu, Shimao Song, Chunhe Yu, Tongwei Zeng, Peng Shen, Li State Grid Liaoning Electric Power Co. Ltd. Liaoning Electric Power Research Institute Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China State Grid Liaoning Electric Power Co. Ltd. Shenyang China

ISBN: (纸本)9781728149301

Abnormal state accumulation over a long period will cause an electrical equipment fault. Therefore, Substation equipment state forecasting plays a vital role in smart grids. Fault forecasting method based on deep learning have been put forward in recent years, but they have deficiencies dealing with temporal features. This paper proposes an abnormal forecasting method for substation equipment based on improved LSTM, and temporal features of power equipment fault can be extracted effectively for a long-time span. The method reads secondary equipment information through SCADA system, then extracts feature to carry out deep learning training. In this paper, RNN and LSTM are firstly compared, and then the structure and algorithm of improved LSTM are given. This method increases coupling between forget gate and cell state compared with the standard LSTM structure, so as to make better use of information at previous moment. Meanwhile problems of network training and overfitting are discussed. Experiments are conducted to demonstrate that improved LSTM is capable of forecasting accurately the complex electric equipment state with a long forecasting horizon. The accuracy of abnormal state forecasting can reach more than 93% which has a better performance compared with many other methods. © 2019 IEEE.

关键词： SCADA systems

来源：评论

学校读者我要写书评

暂无评论

Dense r-robust formations on lattices

Dense r-robust formations on lattices

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Luis Guerrero-Bonilla David Saldaña Vijay Kumar Division of Decision and Control Systems in the School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Autonomous and Intelligent Robotics Laboratory (AIRLab) Lehigh University Bethlehem PA USA GRASP Laboratory University of Pennsylvania

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

Robot networks are susceptible to fail under the presence of malicious or defective robots. Resilient networks in the literature require high connectivity and large communication ranges, leading to high energy consumption in the communication network. This paper presents robot formations with guaranteed resiliency that use smaller communication ranges than previous results in the literature. The formations can be built on triangular and square lattices in the plane, and cubic lattices in the three-dimensional space. We support our theoretical framework with simulations.

关键词： Lattices Robot kinematics Communication networks Robustness Robot sensing systems Energy consumption

来源：评论

学校读者我要写书评

暂无评论

A study on rotate vector reducer performance degradation based on acoustic emission techniques

A study on rotate vector reducer performance degradation bas...

引用

2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： An, Haibo Liang, Wei Ding, Xiaojian Zhang, Yinlong Tan, Jindong State Key Laboratory of Robotics Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Shenyang Institute of Automation Guangzhou Chinese Academy of Sciences Guangzhou511548 China Fifth Electronic Institute of MIIT Guangzhou510610 China Department of Mechanical Aerospace and Biomedical Engineering University of Tennessee KonxvilleTN37996 United States

ISBN: (纸本)9781728163215

This paper presents a performance degradation analysis for rotate vector (RV) reducer using acoustic emission (AE) techniques. Unlike the AE signals from fixed gear reducer that are steady and have unchanged route, the AE signals from RV reducer have variant propagation paths and strengths. This work investigates the kinematics model using AE techniques to solve the inherent issues of RV reducer performance degradation analysis, such as signal variabilities and inappropriate thresholds. Firstly, the propagation path of AE signals within the crankshaft is developed. Secondly, the attenuation trend of AE signals is exponentially formulated based on the corresponding propagation curve. The proposed method has been evaluated on the developed RV reducer platform. AE signals were collected under various working conditions, i.e., four abrasion states with eight types of loads and five rotation speeds. The experimental analysis on typical parameters (e.g., signal energies) proves the effectiveness and accuracy of the developed method based on AE techniques. © 2019 IEEE.

关键词： Crankshafts

来源：评论

学校读者我要写书评

暂无评论

Implementation of CAPI and Traditional PCIe and Delay of Comparison

Implementation of CAPI and Traditional PCIe and Delay of Com...

引用

IEEE International Conference on Cloud Computing and Big Data Analysis (ICCCBDA)

作者： Fudong Wang Tao Zhang Bingjie Zhao Fan Yang Qingxin Li Ziyang Li Key Laboratory of Networked Control Systemsm Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Liaoning Shenyang China Chinese Academy of Sciences Dalian University of Technology Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Liaoning Shenyang China

ISBN: (数字)9781728160245

ISBN: (纸本)9781728160252

With the development of artificial intelligence technology and heterogeneous computing, heterogeneous communication speed is becoming more and more important. The latency of transmitting data determines whether a heterogeneous computing architecture is available. Current acceleration cards usually use PCIe interface. IBM developed the CAPI communication architecture for heterogeneous computing. This paper compares the technical principles and delays of the Power CAPI architecture and a high speed PCIe communication method.

关键词： Field programmable gate arrays Kernel Computer architecture Acceleration Linux Hardware

来源：评论

学校读者我要写书评

暂无评论

Blockchain-based Dependable Task Offloading and Resource Allocation for IIoT via Multi-Agent Deep Reinforcement Learning

Blockchain-based Dependable Task Offloading and Resource All...

引用

IEEE Conference on Vehicular Technology (VTC)

作者： Peifeng Zhang Chi Xu Changqing Xia Xi Jin 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 University of Chinese Academy of Sciences Beijing China

Task offloading and resource allocation are fundamental and crucial for the edge computing-enhanced industrial Internet of things, where the security and credibility among massive heterogeneous devices are being challenged. This paper first proposes a novel blockchain consensus scheme named replicated and Byzantine fault tolerant, which can enhance the trust among nodes with the low communication cost. Then, with the objective of minimizing the task completion time, which includes credible verification, task offloading and transaction record, a joint task offloading and resource allocation problem with respect to blockchain verification ratio, offloading decision, communication and computing resources is formulated. Due to its non-convexity and the decentralized characteristic of blockchain, a multi-agent deep reinforcement learning algorithm with deterministic policy gradient is proposed to appropriate the optimal solution. Experiment results confirm the effectiveness of the proposed scheme in guaranteeing the timeliness and security.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An optimization Strategy for Deep Neural Networks Training

An optimization Strategy for Deep Neural Networks Training

引用

Image Processing, Computer Vision and Machine Learning (ICICML), International Conference on

作者： Tingting Wu Peng Zeng Chunhe Song 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 University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665464697

Learning rate is one of the essential hyperparameters influencing the training process and the accuracy of deep neural networks. However, until now, it is challenging to determine an optimal learning rate. A large learning rate can accelerate the training process but may bring instability in the training process and miss the global optimum. In contrast, a small learning rate would be in a stable training process, but the training speed would be slow, and the training process is easy to fall into local optimum. In this paper, first, the impact of the learning rate is analyzed. It is found that a learning rate schedule should consist of two stages to take into account the speed and accuracy of the training process simultaneously. Based on this consideration, this paper proposes an improvement strategy of learning rate schedules: a two-stage integration strategy of a large fixed learning rate and a rapid decay learning rate. Second, the proposed strategy is applied to optimize a series of widely used learning rate settings. Extensive experiments on CIFAR-10 and CIFAR-100 datasets with VGG19, ResNets, ResNext, DenseNets, SeNet, and some other models demonstrate that the proposed strategy optimizes the learning rate settings, the performance of trained models is enhanced.

关键词： Training Deep learning Measurement Schedules Computational modeling Neural networks Predictive models

来源：评论

学校读者我要写书评

暂无评论

Accelerometer-based Stroke Length Estimation of Sucker-Rod Pumping System in Smart Field

Accelerometer-based Stroke Length Estimation of Sucker-Rod P...

引用

Chinese Automation Congress (CAC)

作者： Haibo Cheng Haibin Yu Peng Zeng Chunhe Song 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 University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

In smart field, innovative technologies and advanced equipment are used to reduce operating costs, monitor wells conditions, optimize the production and improve economic performance. Stroke length is an important parameter in oilfield. It reflects the working condition of production wells. Accurate and effective measurement of stroke length imposes great impacts on oil production. In this paper, a novel method to efficiently perform drift-free stroke length estimation of sucker-rod pumping system with acceleration sensors is proposed. This method includes two stages of integration and two stages of filtering. First, an band-pass infinite impulse response filter is applied to eliminate the drift and sensing errors of acceleration data collected by accelerometer. Then, an integration is calculated to derive velocity signal with the filtered data. After that, a high-pass filter is performed to remove the DC offset of the velocity. Finally, a periodic velocity signal is selected to perform integration operation to compute the stroke length. The proposed method is validated against a real dataset from an oilfield. The experimental results illustrate that the proposed method can reduce sensing errors, suppress interference, and improve estimation accuracy.

关键词： Acceleration Estimation Band-pass filters Sensors IIR filters Accelerometers Production

来源：评论

学校读者我要写书评

暂无评论

A kind of online self-tuning smith predictor

A kind of online self-tuning smith predictor

引用

IEEE International Conference on Mechatronics and Automation

作者： Xu Chen Fei Meng Xiaopeng Chen Qiang Huang Intelligent Robotics Institute Beijing Institute of Technology Beijing China Beijing Advanced Innovation Center for Intelligent Robots and System Beijing Institute of Technology Beijing China Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Beijing China International Joint Research Laboratory of Biomimetic Key Laboratory of Intelligent Control and Decision of Comp lex System Beijing China

ISBN: (纸本)9781509023974

This paper presents an online self-tuning Smith Predictor for the First Order Plus Dead Time Model (FOPDT). It can tune time delay through oscillated input and output. Realtime phase difference detection is used to obtain the phase difference between the input and the output. An online tuner is used to minimize the phase difference. Once the phase difference is minimized, the exact time delay is completely compensated. Our method is suitable for both systems with constant time delay or variant time delay.

关键词： Delay effects Temperature control Delays Predictive models Oscillators Robots

来源：评论

学校读者我要写书评

暂无评论

A Novel Hybrid Method for Fault Diagnosis of Industrial Equipment Based on Vibration Signals 14

A Novel Hybrid Method for Fault Diagnosis of Industrial Equi...

引用

14th IEEE Global Reliability and Prognostics and Health Management Conference, PHM-Hangzhou 2023

作者： Tao, Sen Wang, Kai Zeng, Peng Yu, Tianda Wu, Hao Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110169 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110169 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Nuclear Power Institute of China Chengdu610213 China State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University Chongqing400044 China

ISBN: (纸本)9798350301359

Industrial equipment reliability is a critical issue that smart manufacturing systems must address. Implementation of online fault diagnosis for industrial equipment is a promising technology that can improve equipment reliability. Vibration analysis is a popular technique for equipment condition monitoring. For the non-linear and non-stationary features of industrial vibration signals, a hybrid model based on wavelet transform (WT), support vector machine (SVM), and grey wolf optimization algorithm (GWO) is proposed. The time-frequency domain features of fault signals are extracted by wavelet transform to solve the non-linearity of signals, and the obtained feature vectors are input into SVM for classification. Aiming at the problem of setting penalty coefficient and kernel function parameters, GWO is introduced to seek hyperparameters by using the hunting principle of wolves. In the experimental part, firstly, the comparison of the GWO-WT-SVM, GWO-SVM and SVM models was carried out. Secondly, Comparison with classical classification algorithms is made. Apparently, the GWO-WT-SVM model achieves higher accuracy than other models in bearing fault diagnosis. © 2023 IEEE.

关键词： component Fault diagnosis GWO PHM SVM

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52页 << < 30 31 32 33 34 35 36 37 38 39 > >>

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：