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

358 篇 会议
1 篇 期刊文献

馆藏范围

359 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

331 篇 工学
- 209 篇 控制科学与工程
- 164 篇 计算机科学与技术...
- 139 篇 软件工程
- 41 篇 电气工程
- 38 篇 生物工程
- 34 篇 机械工程
- 30 篇 信息与通信工程
- 25 篇 电子科学与技术（可...
- 20 篇 交通运输工程
- 18 篇 生物医学工程（可授...
- 17 篇 化学工程与技术
- 16 篇 动力工程及工程热...
- 12 篇 航空宇航科学与技...
- 11 篇 力学（可授工学、理...
- 9 篇 材料科学与工程（可...
- 9 篇 冶金工程
- 7 篇 建筑学
210 篇 理学
- 146 篇 数学
- 60 篇 系统科学
- 51 篇 统计学（可授理学、...
- 39 篇 生物学
- 20 篇 物理学
- 14 篇 化学
38 篇 管理学
- 21 篇 图书情报与档案管...
- 19 篇 管理科学与工程(可...
- 7 篇 工商管理
12 篇 医学
- 12 篇 临床医学
- 11 篇 基础医学(可授医学...
- 10 篇 药学(可授医学、理...
9 篇 法学
- 6 篇 法学
6 篇 农学
3 篇 教育学
1 篇 经济学

主题

13 篇 reinforcement le...
12 篇 multi agent syst...
8 篇 deep learning
7 篇 failure analysis
7 篇 generative adver...
7 篇 machine learning
6 篇 lyapunov functio...
5 篇 time delay
5 篇 sliding mode con...
5 篇 state estimation
5 篇 predictive contr...
5 篇 controllers
4 篇 learning systems
4 篇 cyber physical s...
4 篇 anomaly detectio...
4 篇 defects
4 篇 neural networks
4 篇 iterative method...
4 篇 process control
4 篇 predictive model...

机构

6 篇 college of contr...
5 篇 college of artif...
5 篇 university of ch...
5 篇 college of infor...
4 篇 school of electr...
4 篇 school of electr...
4 篇 school of intell...
4 篇 college of infor...
4 篇 school of electr...
3 篇 school of inform...
3 篇 center for robot...
3 篇 school of inform...
3 篇 college of engin...
3 篇 school of mathem...
3 篇 kunming universi...
3 篇 engineering rese...
3 篇 institute of com...
3 篇 school of automa...
3 篇 control and simu...
3 篇 qingdao univ sci...

作者

10 篇 huang deqing
6 篇 chi ronghu
5 篇 li xiangyang
5 篇 ai wei
5 篇 chen zengqiang
5 篇 yang ying
5 篇 sun mingwei
5 篇 lu renquan
5 篇 ren hongru
4 篇 jiao xuguo
4 篇 liu xia
4 篇 liu yan
4 篇 yao wenlong
4 篇 liu shida
4 篇 ge zhiqiang
4 篇 yu wei
4 篇 wang yu
4 篇 wang xin
4 篇 hou zhongsheng
4 篇 liu shan

语言

350 篇 英文
9 篇 其他

检索条件"任意字段=10th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2021"

共 359 条记录，以下是301-310 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 data-driven Intelligent Medical Management System via Neural Networks 10

A Data-Driven Intelligent Medical Management System via Neur...

引用

10th ieee data driven control and learning systems conference, ddcls 2021

作者： Yang, Jinhui Wang, Jianhui Cheng, Xuhong Guo, Zhiwei Shen, Yu Gao, Xu National Research Base of Intelligent Manufacturing Service Chongqing Technology and Business University Chongqing400067 China School of Artificial Intelligence Chongqing Technology and Business University Chongqing400067 China Chongqing South-to-Thais Environmental Protection Technology Research Institute Co. Ltd. Chongqing400069 China Chongqing Sino French Environmental Excellence Research Development Center Co. Ltd. Chongqing400050 China

ISBN: (纸本)9781665424233

For human health, medical diagnosis plays an irreplaceable role, conventional medical diagnosis methods cannot ensure the accuracy of diagnosis due to the interference of various external factors. therefore, this paper proposes a data-driven intelligent medical management system via neural networks(MMS-ID). the essence of this method is to predict the survival time of cancer patients with the aid of gradient boosting decision tree (GBDT) and hybrid neural network model. Firstly, GBDT screens the feature factors of matching conditions according to the set value domain, and inputs them into the neural network. Subsequently, a hybrid neural network that combines the convolutional neural network (CNN) and the long short-term memory (LSTM) model is employed to predict survival length of cancer patients. Finally, the stability of MMS-ID is analyzed and compared with a series of baseline methods. A series of experiments prove that MMS-ID has excellent performance. © 2021 ieee.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

Yarn-Dyed Shirt cut Pieces Defect Detection Using Attention Vector Quantized-Variational Autoencoder 10

Yarn-Dyed Shirt cut Pieces Defect Detection Using Attention ...

引用

10th ieee data driven control and learning systems conference, ddcls 2021

作者： Zhang, Hongwei Liu, Shuting Ge, Zhiqiang Li, Pengfei Xi'an Polytechnic University Institute of Machine Vision and Intelligent Detection ShaanXi Xi'an710048 China Zhejiang University State Key Laboratory of Industrial Control Technology ZheJiang Hangzhou310027 China

ISBN: (纸本)9781665424233

For yarn-dyed shirt cut defects detection problems in production process, this paper proposes a yarn-dyed shirt cut defects detection method based on attention vector-quantized variational autoencoder reconstructed model and residual analysis. To solve the actual problem that the defect sample quantity scarce, defect categories imbalances, high cost and poor generalization ability of artificial design defect features. Firstly, for a certain yarn-dyed shirt cut, salt and pepper noise is artificially added to the defect-free samples to construct a training data set, and then a reconstruction model based on the attention vector quantized variational autoencoder is established and trained. Secondly, a residual map between the original image and the correspondingly reconstructed image is calculated. Finally, the defective area could be detected and located by thresholding and opening operation processing. Experimental results on several yarn-dyed shirt cut pieces data sets show that the proposed method can effectively reconstruct the yarn-dyed shirt cut pieces, detect and locate the defect area of yarn-dyed shirt cut pieces quickly. © 2021 ieee.

关键词： Defects

来源：评论

学校读者我要写书评

暂无评论

Multi-Player Robust control of Stackelberg Games via Adaptive Dynamic Programming 11

Multi-Player Robust Control of Stackelberg Games via Adaptiv...

引用

11th ieee data driven control and learning systems conference, ddcls 2022

作者： Zhang, Yongwei Zhang, Shunchao Zhao, Bo Liu, Derong Guangdong University of Technology School of Automation Guangzhou510006 China Beijing Normal University School of Systems Science Beijing100875 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

In this paper, the hierarchical optimization problem of multi-player systems with matched uncertainties is investigated via adaptive dynamic programming. In the hierarchical optimization problem, there exist one leader and multiple followers, the leader chooses a policy in advance based on the actions of the followers, and the followers make optimal responses to the leader's policy. the optimal policies of the leader and the followers form the Stackelberg equilibrium. By designing appropriate value functions for the leader and the followers, the hierarchical optimization problem is formulated as a Stackelberg game and the robust stabilization problem is transformed into an optimal regulation problem. Moreover, the critic-only structure is established to obtain the approximate Stackelberg equilibrium. theoretical analysis shows that the developed ADP-based robust control guarantees the closed-loop system to be asymptotically stable. Finally, simulation example is adopted to verify the effectiveness of the present scheme. © 2022 ieee.

关键词： Robust control

来源：评论

学校读者我要写书评

暂无评论

Compressor Health Prediction Based on Multi-Source Information Fusion and LSTM 10

Compressor Health Prediction Based on Multi-Source Informati...

引用

10th ieee data driven control and learning systems conference, ddcls 2021

作者： Tian, Huixin Yang, Linzheng Wang, Hongyi Li, Kun School of Control Science and Engineering Tiangong University Tianjin300387 China Key Laboratory of Advanced Electrical Engineering and Energy Technology Tiangong University Tianjin300387 China Tianjin Jingcheng Technology Development Co. Ltd Tianjin300110 China School of Economics and Management Tiangong University Tianjin300387 China

ISBN: (纸本)9781665424233

Reciprocating compressor is core equipment of petrochemical industry. Accurate state of health monitoring and faults early warning state are very important for the smooth running of a reciprocating compressor. Aiming at the lower accuracy of traditional vibration signal prediction, the LCD-LSTM is used for the accurate and stable vibration signal prediction. the LCD is used to decompose the original vibration signal into many intrinsic scale components(ISCs). And all of the ISCs are predicted by LSTM separately and accumulated as vibration signal predicted result. Meanwhile, in order to overcome the limitation of information in single vibration signal, a multi-source information fusion (MSIF) strategy is designed to build the state of health prediction model with more comprehensive information by considering multiple parameters information related to the main faults. then a health curve which will reflect and predict the running state of compressor can be obtained. To validate the prediction capacity of the proposed MSIF-LCD-LSTM method, running data of the reciprocating compressor in offshore natural gas exploitation of China National Offshore Oil Corporation is used for modeling and testing. the results of experiments demonstrate that the proposed model has great superiority over other models and good performance of running state detection and faults early warning. © 2021 ieee.

关键词： Health

来源：评论

学校读者我要写书评

暂无评论

A Train Cooperative Operation Optimization Method Considering Passenger Comfort based on Reinforcement learning 11

A Train Cooperative Operation Optimization Method Considerin...

引用

11th ieee data driven control and learning systems conference, ddcls 2022

作者： Wang, Xingguo Wu, Yue Huang, Deqing Zhu, Lei Lu, Zheng He, Yan Institute of System Science and Technology School of Electrical Engineering Southwest Jiaotong University Chengdu611756 China Southwest Jiaotong University Key Laboratory of Advanced Energy Traction Comprehensive Energy Saving Railway Industry Chengdu610031 China School of Computing and Artificial Intelligence Southwest Jiaotong University Chengdu611756 China School of Design Arts Southwest Jiaotong University Chengdu610031 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

this paper mainly focuses on the high-speed train cooperative operation problem, considering passenger comfort. To solve this problem, a speed curve optimization method based on Reinforcement learning algorithm is proposed. First, according to the train dynamics system, we build the speed curve optimization object. For realizing the train cooperative operation and increasing the passenger comfort, trains distance constraint and jerk rate constraint are fully considered in formulating reward function. And then, agent of Twin Delayed Deep Deterministic Policy Gradient (TD3) is established. Based on TD3 algorithm, two groups of Q-value networks and one group of action action networks have the same structure, different initial values and update rates respectively, which improves the stability and convergence speed of the algorithm. After the training. the Agent can generate a desirable speed curve of train based on constraints of vehicle output and jerk rate under cooperative operation. © 2022 ieee.

关键词： Speed

来源：评论

学校读者我要写书评

暂无评论

LS-SVM Combined with ZNN for Predicting the Continuous Motion Joint Angle of Lower Limb 10

LS-SVM Combined with ZNN for Predicting the Continuous Motio...

引用

10th ieee data driven control and learning systems conference, ddcls 2021

作者： Zhang, Xin Liu, Keping Li, Chunxu Yi, Jiang Duan, Xiaoqin Sun, Zhongbo Changchun University of Technology Department of Control Engineering Changchun130000 China University of Plymouth Centre for Robotics and Neural Systems PlymouthPL48AA United Kingdom Medicine of the Second Hospital of Jilin University Department of Rehabilitation Changchun130000 China

ISBN: (纸本)9781665424233

In this paper, a method fusing least squares support vector machine (LS-SVM) with Gaussian kernel function and zeroing neural network (ZNN) is proposed to forecast the continuous motion of lower limb. the surface electromyography (sEMG) signal contains human behavior information and directly reflects the movement intention. In the experiment, the sEMG signal of the lower limbs when the tester is doing leg extension exercise is collected and the real knee joint angle is recorded at the same time. then the raw sEMG is subjected to a series of preprocessing, and the corresponding muscle activation is gained by calculation. the muscle activation is used as input to the LS-SVM model, and the output to the model is the knee joint angle. LS-SVM transforms the original problem into solving linear equations. When the amount of data is relatively large, the traditional solution method is very time-consuming, and the proposed ZNN method is able to solve the problem, thus speeding up the convergence speed and greatly reducing the learning time. Finally, the back propagation neural network (BPNN) model is utilized to form a comparative experiment. the numerical results indicate that a more stable and better performance is reflected in the raised method, which provides a valuable reference for the research of joint continuous estimation. © 2021 ieee.

关键词： Numerical methods

来源：评论

学校读者我要写书评

暂无评论

Fractional-Order New Generation of 6k+1-Order Repetitive control for three-phase Grid-connected Converters 10

Fractional-Order New Generation of 6k+1-Order Repetitive Con...

引用

10th ieee data driven control and learning systems conference, ddcls 2021

作者： Wang, Wei Lu, Wenzhou Zhou, Keliang Fan, Qigao School of Internet of Things Engineering Jiangnan University Wuxi214122 China School of Automation Wuhan University of Technology Wuhan430070 China

ISBN: (纸本)9781665424233

this paper proposed a fractional-order new generation of 6k\pm 1-order repetitive control scheme (FO-NG-6k\pm 1 RC). FO-NG-6k\pm 1 RC is composed of NG-6k\pm 1 RC and a Farrow structure fractional delay filter based on Taylor series expansion. Since 6 k\pm 1 RC/FO-NG 6k\pm 1 RC occupies less digital memory space, it has better dynamic performance than CRC/FO-CRC, which is more suitable for the control of three-phase power systems dominated by the 6k\pm 1-order harmonics. By updating filter coefficients online in real time, FO-NG-6k\pm 1 RC can quickly and effectively deal with the frequency variations of grid-connected converters, and has good frequency adaptability. through a simulation example applied to a three-phase grid-connected inverter, the effectiveness and superiority of the proposed FO-NG-6k\pm 1 RC control scheme are fully verified. © 2021 ieee.

关键词： Power converters

来源：评论

学校读者我要写书评

暂无评论

Yarn-dyed Shirt Piece Defect Detection Based on U-shaped Swin Transformer Auto-encoder 11

Yarn-dyed Shirt Piece Defect Detection Based on U-shaped Swi...

引用

11th ieee data driven control and learning systems conference, ddcls 2022

作者： Zhang, Hongwei Xiong, Wenbo Zhang, Weiwei Lu, Shuai School of Electronic and Information Xi'an Polytechnic University Xi'an710048 China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China School of Medical Technology Beijing Institute of Technology Beijing100081 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

Automatic defect detection is an essential and challenging problem in the yarn-dyed weaving production process, this paper proposed a novel U-shaped Swin Transformer auto-encoder reconstructed model for yarn-dyed shirt piece defect detection. this method uses the model of Transformer to extract the global features of the image better and reconstruct it more accurately, which solves the problems of scarce and unbalanced type of defect samples and high cost in actual production. Firstly, for a certain pattern, using defect-free samples adding Gaussian noise to train the reconstruction model. then, the image to be tested is input into the Transformer model to obtain the corresponding output image. Subsequently, the residual image is calculated by subtracting the input image and its corresponding output image. Finally, the defect localization can be achieved through thresholding and morphological operation. the experiment result verifies the effectiveness of the proposed method on various types of yarn-dyed shirt pieces. © 2022 ieee.

关键词： Yarn

来源：评论

学校读者我要写书评

暂无评论

the Classification of Motor Imagery EEG Signals Based on the Time-Frequency-Spatial Feature 10

The Classification of Motor Imagery EEG Signals Based on the...

引用

10th ieee data driven control and learning systems conference, ddcls 2021

作者： Deng, Xin Zhang, Boxian Liu, Ke Wang, Jin Yang, Pengfei Hu, Chengxin Key Laboratory of Data Engineering and Visual Computing College of Computer Science and Technology Chongqing University of Posts and Telecommunication Chongqing400065 China

ISBN: (纸本)9781665424233

the effective features of the motor imagery (MI) electroencephalogram (EEG) signals plays a significant role to improve the classification accuracy for the brain-computer interface (BCI) system. Some traditional methods usually extract the frequency or spatial features without considering the related information between different channels that would affect the classification performance. this paper proposes a new method for feature extraction of EEG signals based on the fusion of time-frequency and spatial features. At the beginning, the common spatial pattern (CSP) algorithm is adopted to extract the spatial features. then the discrete wavelet transform (DWT) and the wavelet packet decomposition (WPD) are used to extract the μ rhythm of the motor imagery EEG signals as the time-frequency features. After that, by combining the spatial and time-frequency features, the time-frequency-spatial feature is formed. Based on different kinds of features, the experimental data are classified by using the support vector machine (SVM), as well as the sparse representation classification (SRC) algorithm with the elastomeric network (EN) and L1 norm, respectively. the experimental results show that the SRC with EN has a better performance on either the time-frequency feature or spatial feature than the SRC with L1 norm does. In contrast, the SVM and the SRC with Ll norm perform better than the SRC with EN based on the time-frequency-spatial feature. the study concludes that the time-frequency-spatial feature cooperating with the certain classifiers can achieve the good classification effect for the MI EEG signals, which not only reduces the operation time but also improves the classification accuracy. © 2021 ieee.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

A Multi-stage Optimized Fault Diagnosis Model for Imbalanced Fault data in Manufacturing Process 11

A Multi-stage Optimized Fault Diagnosis Model for Imbalanced...

引用

11th ieee data driven control and learning systems conference, ddcls 2022

作者： Lai, Zhouhao Dong, Yan Ren, Hongru Lu, Renquan Guangdong University of Technology School of Computer Science and Technology and Guangdong Province Key Laboratory of Intelligent Decision and Cooperative Control Guangzhou510006 China Guangdong University of Technology School of Automation and Guangdong Province Key Laboratory of Intelligent Decision and Cooperative Control Guangzhou510006 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

Fault diagnosis of equipment in the manufacturing process is particularly important, and it is an indispensable link in intelligent manufacturing. the fault data generated by the equipment during the manufacturing process is often imbalanced. However, modeling and training on imbalanced dataset will result in a very high rate of misclassification. In order to solve this problem, and improve the accuracy of fault diagnosis in the manufacturing process. this paper proposes a multi-stage optimizatied fault diagnosis model based on bayesian optimization, synthetic minority oversampling technique(SMOTE) and stagewise additive modeling using a multi-class exponential loss function(SAMME), namely the BSS model. the multi-stage optimized fault diagnosis model proposed in this paper improves the diagnosis accuracy of imbalanced fault dataset from the aspects of dataset processing, model building and model training. Finally, the results of ultrasonic flowmeter failure diagnosis show that among the various evaluation indicators, the multi-stage optimized fault diagnosis model proposed in this paper is better than the traditional single machine learning model. © 2022 ieee.

关键词： Failure analysis

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36页 << < 27 28 29 30 31 32 33 34 35 36 > >>

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：