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

474 篇 会议

馆藏范围

474 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

361 篇 工学
- 245 篇 计算机科学与技术...
- 180 篇 电气工程
- 156 篇 控制科学与工程
- 41 篇 软件工程
- 11 篇 机械工程
- 11 篇 生物医学工程（可授...
- 10 篇 信息与通信工程
- 10 篇 生物工程
- 9 篇 仪器科学与技术
- 9 篇 动力工程及工程热...
- 8 篇 交通运输工程
- 6 篇 安全科学与工程
- 6 篇 网络空间安全
- 4 篇 土木工程
- 3 篇 力学（可授工学、理...
- 3 篇 冶金工程
- 3 篇 电子科学与技术（可...
- 3 篇 建筑学
- 3 篇 石油与天然气工程
- 3 篇 航空宇航科学与技...
138 篇 理学
- 101 篇 系统科学
- 33 篇 数学
- 12 篇 生物学
- 9 篇 统计学（可授理学、...
- 8 篇 化学
- 6 篇 物理学
21 篇 管理学
- 19 篇 管理科学与工程(可...
- 10 篇 图书情报与档案管...
- 5 篇 工商管理
5 篇 医学
- 5 篇 临床医学
2 篇 经济学
2 篇 法学
2 篇 教育学
1 篇 军事学

主题

47 篇 iterative learni...
41 篇 mathematical mod...
31 篇 data models
23 篇 convergence
23 篇 control systems
23 篇 nonlinear system...
22 篇 trajectory
16 篇 predictive model...
16 篇 fault detection
16 篇 adaptation model...
15 篇 deep learning
14 篇 uncertainty
14 篇 training
13 篇 reinforcement le...
13 篇 closed loop syst...
13 篇 adaptive control
12 篇 optimization
12 篇 heuristic algori...
11 篇 stability analys...
11 篇 feature extracti...

机构

10 篇 qingdao univ sci...
7 篇 north china univ...
6 篇 qingdao univ sci...
6 篇 beijing key lab ...
5 篇 beijing univ che...
5 篇 beijing jiaotong...
4 篇 beijing inst tec...
4 篇 qingdao univ sci...
4 篇 zhejiang univ te...
3 篇 qingdao univ sci...
3 篇 college of contr...
3 篇 school of automa...
3 篇 nankai univ coll...
3 篇 research center ...
3 篇 school of mathem...
3 篇 jiangnan univ sc...
3 篇 school of electr...
3 篇 jiangnan univ in...
3 篇 qingdao univ sci...
3 篇 changchun univer...

作者

10 篇 chi ronghu
8 篇 ronghu chi
8 篇 hou zhongsheng
7 篇 zhongsheng hou
6 篇 liu yang
6 篇 wang li
6 篇 li wang
5 篇 liu keping
5 篇 deqing huang
5 篇 lu renquan
5 篇 zhihuan song
5 篇 ren hongru
5 篇 sun zhongbo
5 篇 huang deqing
5 篇 zhang ruikun
4 篇 xingping liu
4 篇 su hongye
4 篇 xie lei
4 篇 song zhihuan
4 篇 liu yi

语言

460 篇 英文
9 篇 中文
5 篇 其他

检索条件"任意字段=7th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2018"

共 474 条记录，以下是431-440 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 Statistical learning Approach for Cable-driven Robot in Rehabilitation Training 7

A Statistical Learning Approach for Cable-driven Robot in Re...

引用

7th ieee International conference on Advanced Robotics and Mechatronics

作者： Zheng, Jianlin Xie, Chenglin Song, Rong Xu, Ting Sun Yat Sen Univ Guangdong Prov Engn & Technol Ctr Adv & Portable Guangzhou Guangdong Peoples R China Sun Yat Sen Univ Sch Biomed Engn Key Lab Sensing Technol & Biomed Instrument Guang Guangzhou Guangdong Peoples R China

ISBN: (数字)9781665483063

ISBN: (纸本)9781665483063

Cable-driven rehabilitation robots can be used to recover the upper-limb motor function of hemiplegia patients after stroke. In this study, a statistical approach was proposed to enable a 3-DOF upper-limb cable-driven rehabilitation robot (UCDRR) to predict the human intention by learning human skills from demonstrations. Specifically, in the learning phase, Gaussian mixture model (GMM) was exploited to statistically analyze the human-robot interaction features (i.e., Electromyography (EMG) and interaction force) based on the recorded demonstrator-robot interaction data. then, during prediction, the robot estimated the interaction force from the measured EMG by using Gaussian mixture regression (GMR). the experimental results of the interaction force prediction in simulation demonstrated that the proposed approach could statistically extract the variable information from the multiple demonstrations successfully and estimate subject-robot interaction forces with high accuracy. this study will help the UCDRR to provide assistance as needed to hemiplegia patients during rehabilitation training, thereby promoting the active participation.

关键词： Training Mechatronics Force Statistical learning Robot control Human-robot interaction Stroke (medical condition)

来源：评论

学校读者我要写书评

暂无评论

Fast Probabilistic TTC Assessment Based on Copula theory and Deep Ensemble learning 7

Fast Probabilistic TTC Assessment Based on Copula Theory and...

引用

7th Asia conference on Power and Electrical Engineering, ACPEE 2022

作者： Zhang, Shaopeng Yan, Jiongcheng Li, Xin Yang, Dong Ma, Huan Li, Changgang Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong Jinan China State Grid Shandong Electric Power Company Shandong Jinan China Electric Power Research Institute State Grid Shandong Electric Power Company Shandong Jinan China

ISBN: (纸本)9781665418195

Wind power integration makes the uncertainty of power system increasing dramatically, which brings new challenges to the calculation of Total Transfer Capability (TTC). A fast assessment method for probabilistic TTC based on Copula and deep ensemble learning is proposed. Considering wind power output uncertainties and correlation of wind speed in geographical close wind farms, Copula function is adopted to generate scenarios. Stacked Denoising Autoencoder (SDAE) is used to extract features directly from source data. Support Vector Regression (SVR) is selected as regressor and bagging ensemble strategy is applied to further improve the accuracy of the TTC estimation. the case study in simplified Shandong grid validates the effectiveness of the proposed method. © 2022 ieee.

关键词： learning systems

来源：评论

学校读者我要写书评

暂无评论

A new deep learning-based food recognition system for mobile terminal

A new deep learning-based food recognition system for mobile...

引用

data driven control and learning systems (ddcls)

作者： Wenze Chen Ruizhuo Song School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing

With the improvement of people's health awareness, people pay more attention to their health. In recent years, the intelligent health management system based on food recognition technology has become popular, which can help users maintain healthy eating habits. However, applying the current deep learning method in mobile phones and other terminal devices is difficult, mainly because the terminal devices have the low computing power and the network needs to perform many calculations during operation. In this paper, we have adopted the methods of parameter reconstruction and calculation graph fusion to reduce the network computing load so that it can run in real-time in terminal devices, and the detection speed on Snapdragon 778G SOC exceeds 7 FPS. Besides, experiments on the VIPER-FoodNet (VFN) dataset show that our model has a high mean average precision (mAP) of 9.17% compared with the current advanced model.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Self-learning Constellation Mapping Method Based on Neural Networks 7

Self-learning Constellation Mapping Method Based on Neural N...

引用

7th International conference on Information Science and control Engineering, ICISCE 2020

作者： Luo, Yingzhe Hu, Jianhao University of Electronic and Science Technology of China National Key Laboratory of Science and Technology on Communications Chengdu China

ISBN: (纸本)9781728164069

Neural networks have been gained extensive study and application in the communication systems. this paper applies the neural networks to the transmitter, which proposes a self-learning constellation mapping method. the proposed method contains two kinds of neural networks. One is used to generate a new constellation mapping which can compensate the channel distortion. the other one is used to determine whether the newly generated constellation mapping is optimal. these two types of neural networks constitute an actor-critic architecture which is trained through the reinforcement learning method. Without losing generality, this paper applies the proposed method to the quadrature amplitude modulation systems. In the simulation experiments, the proposed method can generate some new quadrature amplitude modulation constellation diagrams which can compensate in advance the amplitude and phase distortion caused by the channel. Moreover, the performance of the proposed method is superior to the classical compensation method. Significantly, the neural networks in the proposed method are trained online, so there is no need to prepare a large amount of artificial data sets in the training phase. © 2020 ieee.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Research on Fault Self-Healing control Method of Intelligent Power Distribution System Based on Deep learning 7

Research on Fault Self-Healing Control Method of Intelligent...

引用

7th ieee conference on Energy Internet and Energy System Integration, EI2 2023

作者： Li, Jingru Jiang, Shigong Li, Hongjun Chai, Wei Fo, Jiacheng Luo, Fengzhang Ge, Nan Wang, Shengyuan State Grid Economic and Technological Research Institute Co. Ltd. Beijing102200 China State Grid Economic and Technological Research Institute Co. Ltd. Distribution Network Planning Center Beijing102200 China Electric Power Research Institute State Grid Shanghai Municipal Electric Power Company Shanghai200080 China Tianjin University Key Laboratory of Smart Grid of Ministry of Education Tianjin300072 China

ISBN: (纸本)9798350345094

Aiming at the deficiencies of the current distribution network self-healing control, the high time cost of the heuristic algorithm in the recovery control algorithm after fault isolation and the insolvability arising from the intelligent optimization algorithm in finding fault recovery generation strategies, the traditional distribution network self-healing control scheme cannot meet the application requirements of intelligent distribution systems. this paper proposes a data-driven fault recovery strategy for distribution networks. Firstly, a distribution network self-healing control model based on the mechanism model is proposed, and the distribution network reconstruction method is used to realize the distribution network self-healing function. Finally, the effectiveness of the self-healing control model is verified through the simulation analysis of the ieee 33-node system case, which demonstrates the advantages of the proposed strategy in generating self-healing control solutions for distribution networks quickly and improving network reconfiguration efficiency. © 2023 ieee.

关键词： Electric power distribution

来源：评论

学校读者我要写书评

暂无评论

Hand Gesture Classification in Transradial Amputees Using the Myo Armband Classifier 7

Hand Gesture Classification in Transradial Amputees Using th...

引用

7th ieee International conference on Biomedical Robotics and Biomechatronics (BIOROB)

作者： Cognolato, M. Atzori, M. Faccio, D. Tiengo, C. Bassetto, F. Gassert, R. Mueller, H. Univ Appl Sci Western Switzerland HES SO Valais Informat Syst Inst Sierre Switzerland Swiss Fed Inst Technol Dept Hlth Sci & Technol Rehabil Engn Lab Zurich Switzerland Padova Univ Hosp Clin Plast Surg Padua Italy

ISBN: (纸本)9781538681831

Dexterous hand prostheses controlled via surface electromyography represent the most advanced non invasive functional restorative solution for hand amputees. However, control difficulties, comfort problems and high costs are still the main limitations of such commercial devices. the high cost can represent a barrier that is difficult to overcome, especially for pediatric populations and in developing countries. Low-cost technology was successfully used in the hand prosthetics field in recent years. In previous work, a low-cost gesture recognition armband called Myo showed promising results for hand gesture classification tasks in intact subjects. Most of these applications were based on machine learning techniques applied to the Myo raw data. However, the classifier provided with the Myo is able to identify five hand gestures, providing capabilities as a myoelectric control system. No studies have quantitatively investigated its performance in subjects with hand amputation, yet. the aim of this study is to quantitatively evaluate the performance of the Myo hand gesture classifier in hand amputees. three subjects with hand amputation were asked to attempt performing the five pre-set hand gestures. Each gesture was repeated three times with the arm in three different postures. the subjects did not perform any training and did not receive any feedback. Overall classification accuracy for the four hand gestures based on electromyographic data ranged between 50% and 97%. A clear relation between the length of the residual limb and the classification accuracy was observed. the results show that the Myo built-in classifier can provide good performance when tested on hand amputees, supporting its applicability as a low-cost myoelectric control system.

关键词： Prosthetics Gesture recognition Performance evaluation Calibration Electromyography control systems Electrodes

来源：评论

学校读者我要写书评

暂无评论

Dow Jones Trading with Deep learning: the Unreasonable Effectiveness of Recurrent Neural Networks 7

Dow Jones Trading with Deep Learning: The Unreasonable Effec...

引用

7th International conference on data Science, Technology and Applications, data 2018

作者： Fabbri, Mirco Moro, Gianluca University of Bologna Via Cesare Pavese CesenaI-47522 Italy

ISBN: (纸本)9789897583186

though recurrent neural networks (RNN) outperform traditional machine learning algorithms in the detection of long-term dependencies among the training instances, such as in term sequences in sentences or among values in time series, surprisingly few studies so far have deployed concrete solutions with RNNs for the stock market trading. Presumably the current difficulties of training RNNs have contributed to discourage their wide *** work presents a simple but effective solution, based on a deep RNN, whose gains in trading with Dow Jones Industrial Average (DJIA) outperform the state-of-the-art, moreover the gain is 50% higher than that produced by similar feed forward deep neural networks. the trading actions are driven by the predictions of the price movements of DJIA, using simply its publicly available historical series. To improve the reliability of results with respect to the literature, we have experimented the approach on a long consecutive period of 18 years of historical DJIA series, from 2000 to 2017. In 8 years of trading in the test set period from 2009 to 2017, the solution has quintupled the initial capital, moreover since DJIA has on average an increasing trend, we also tested the approach with a decreasing averagely trend by simply inverting the same historical series of DJIA. In this extreme case, in which hardly any investor would risk money, the approach has more than doubled the initial capital. Copyright © 2018 by SCITEPRESS-Science and Technology Publications, Lda. All rights reserved.

关键词： Financial markets

来源：评论

学校读者我要写书评

暂无评论

Modeling and Optimizing Building HVAC Energy systems Using Deep Neural Networks 7

Modeling and Optimizing Building HVAC Energy Systems Using D...

引用

7th International conference on Smart Grid and Clean Energy Technologies (ICSGCE)

作者： Deng, Jiahao Wang, Haoran Depaul Univ Coll Comp & Digital Media Chicago IL 60604 USA Arris Int Sunnyvale CA 94089 USA

ISBN: (纸本)9781538667965

the heating, ventilating and air conditioning (HVAC) systems consumes more than half of the building energy consumption. An efficient HVAC system ensures the comfortable living and working environment. In this research, we proposes a novel approach to maximize the HVAC system efficiency regarding a typical office-type facility. One year energy data is collected from a commercial building in Chicago, IL for this research. the future room temperature and air humidity are predicted by deep neural networks. Deep neural network is also selected to extract the highly non-linear relationship between the control settings and the energy utility. A comparative analysis between the deep neural network and other state-of-arts data driven models is conducted. the deep neural networks outperforms the other algorithms and is applied to model the room temperature and air humidity. the predicted temperature and humidity are integrated into an energy optimization algorithm. through numerical experiments, the systematic efficiency has been optimized to an acceptable level. Significant energy savings have been obtained while the facility's thermal comfort has been maintained.

关键词： data-driven deep neural network HVAC particle swarm optimization

来源：评论

学校读者我要写书评

暂无评论

Evaluating Machine learning Models Best Fit for Crime Prediction in Windhoek 7

Evaluating Machine Learning Models Best Fit for Crime Predic...

引用

7th International conference on Artificial Intelligence, Big data, Computing and data Communication systems, icABCD 2024

作者： Angondji, Maria Liisa Chitauro, Mercy Shava, Fungai Bhunu Namibia University of Science and Technology Department of Informatics Windhoek Namibia

ISBN: (纸本)9798350387902

Crime refers to any unlawful act which is punishable by law. Crime has a harmful effect on the community, it hinders the economic growth and it causes fears in the society. Crime rates have been on the increase around the world, which led to law enforcement agencies and stakeholders to implement crime prevention approaches such as predictive policing as most of the traditional crime-solving techniques were proven to be incompetent and ineffective. In Namibia, there is a lack of data-driven predictive method for combating crime. Hence, the paper evaluated machine learning (ML) models best fit for predicting crime types in Windhoek. the study employed a quantitative research approach to historical crime data from January 2018 to December 2022. After pre-processing, supervised classification models namely;Random Forest, K-Nearest Neighbors (KNN), Naive Bayes, and Decision Trees were trained and tested on the dataset. Initial findings revealed low accuracy rates across all models due to the imbalanced class distribution within the crime dataset mainly on the target variable which is Type of crime. To tackle the imbalances, various resampling techniques namely, Synthetic Minority Over-sampling Technique (SMOTE), Edited Nearest Neighbor (ENN), SMOTETomek and SMOTEEN were applied, leading to a significant improvement in model performance. the Random Forest model demonstrated superior performance, especially when trained on balanced datasets created through SMOTE and SMOTETomek, achieving an accuracy rate of 84%. the paper highlights the important role of addressing class imbalance through resampling techniques to improve the predictive accuracy of machine learning models in crime prediction. the findings suggest that the Random Forest model, coupled with appropriate resampling methods, provides a robust solution for crime type prediction in Windhoek. © 2024 ieee.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Optimization of Traffic and Time control with Sensor-driven Transmission control System using MANET and Machine learning 7

Optimization of Traffic and Time Control with Sensor-Driven ...

引用

7th International conference on Inventive Computation Technologies, ICICT 2024

作者： Kathirvel, N. Vidyalakshmi, R. Raihana, A. Mohanraj, A. Uma, S. Saranya, N. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science And Technology School of Computing Department of Information Technology India Karpagam College of Engineerng Department of Eee Coimbatore India Sri Krishna College of Engineering And Technology Department of Information Technology Coimbatore India Sri Eshwar College of Engineering Department of Computer Science And Engineering India Hindustan College of Engineering And Technology Department of Computer Science And Engineering India

ISBN: (纸本)9798350359299

In the dynamic landscape of modern urban environments, the optimization of transportation and traffic management systems is paramount for ensuring efficiency, sustainability, and the overall well-being of inhabitants. this study introduces an innovative solution through the deployment of a sophisticated network of strategically positioned sensors at crucial locations, encompassing roadway sections, entry and exit points, and parking spaces within a smart city framework. these sensors continuously capture real-time data on traffic flow, vehicle counts, and parking spot occupancy, forming the foundational elements of an intelligent system. Robust machine learning models, notably Convolutional Neural Networks (CNN), VGG19, k-Nearest Neighbors (KNN), and Support Vector Machines (SVM), are employed to process and analyze the acquired sensor data. CNN, renowned for its prowess in image recognition, emerges as the leading performer, achieving an impressive accuracy of 97.6%. this model excels in deciphering complex spatial patterns, significantly enhancing the precision of traffic forecasts. Additionally, performance metrics, encompassing precision, recall, F1 score, and accuracy, underscore the efficacy of each machine learning model. the exceptional precision and recall values across all models showcase their robustness in identifying and predicting traffic situations, while accuracy scores affirm their overall efficiency in optimizing transportation and traffic management within smart city environments. © 2024 ieee.

关键词： Sensor 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48页 << < 39 40 41 42 43 44 45 46 47 48 > >>

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：