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

7,072 篇 会议
48 篇 期刊文献
39 册 图书

馆藏范围

7,159 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4,920 篇 工学
- 4,107 篇 计算机科学与技术...
- 2,511 篇 软件工程
- 1,065 篇 信息与通信工程
- 791 篇 控制科学与工程
- 662 篇 生物工程
- 657 篇 电气工程
- 423 篇 生物医学工程（可授...
- 286 篇 交通运输工程
- 283 篇 机械工程
- 226 篇 仪器科学与技术
- 226 篇 安全科学与工程
- 205 篇 建筑学
- 199 篇 动力工程及工程热...
- 184 篇 光学工程
- 168 篇 化学工程与技术
- 153 篇 土木工程
1,914 篇 理学
- 1,080 篇 数学
- 717 篇 生物学
- 441 篇 统计学（可授理学、...
- 284 篇 物理学
- 252 篇 系统科学
- 141 篇 化学
1,147 篇 管理学
- 655 篇 管理科学与工程(可...
- 578 篇 图书情报与档案管...
- 314 篇 工商管理
405 篇 医学
- 351 篇 临床医学
- 295 篇 基础医学(可授医学...
- 188 篇 药学(可授医学、理...
244 篇 教育学
- 243 篇 教育学
209 篇 法学
- 195 篇 社会学
119 篇 农学
110 篇 经济学
50 篇 文学
7 篇 艺术学
5 篇 军事学

主题

557 篇 machine learning
458 篇 deep learning
262 篇 training
254 篇 data mining
235 篇 data models
220 篇 feature extracti...
215 篇 accuracy
183 篇 support vector m...
178 篇 predictive model...
138 篇 neural networks
138 篇 machine learning...
130 篇 computational mo...
121 篇 reinforcement le...
107 篇 convolutional ne...
103 篇 real-time system...
92 篇 forecasting
90 篇 artificial intel...
89 篇 learning systems
88 篇 transfer learnin...
87 篇 big data

机构

69 篇 chitkara univers...
17 篇 school of electr...
15 篇 computer science...
14 篇 harbin engineeri...
13 篇 graphic era hill...
12 篇 building civil a...
12 篇 uttaranchal inst...
12 篇 computer science...
11 篇 university of ch...
10 篇 school of electr...
10 篇 school of comput...
10 篇 graphic era deem...
10 篇 school of electr...
10 篇 yonsei univ dept...
9 篇 wuhan university...
9 篇 univ chinese aca...
9 篇 school of inform...
8 篇 school of remote...
7 篇 university of sa...
7 篇 microsoft resear...

作者

17 篇 kukreja vinay
15 篇 vinay kukreja
13 篇 yin hujun
12 篇 liu yang
12 篇 corchado emilio
11 篇 mehta shiva
10 篇 shiva mehta
10 篇 hujun yin
10 篇 cho sung-bae
9 篇 notsu akira
9 篇 silva catarina
9 篇 alhajj reda
7 篇 ksieniewicz pawe...
7 篇 hammer barbara
7 篇 zhang byoung-tak
7 篇 wozniak michal
7 篇 hussain abir
7 篇 soubra hassan
7 篇 huang de-shuang
7 篇 camacho david

语言

6,775 篇 英文
373 篇 其他
28 篇 中文
1 篇 西班牙文
1 篇 俄文

检索条件"任意字段=11th International Conference on Intelligent Data Engineering and Automated Learning"

共 7159 条记录，以下是4361-4370 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：

New Interfaces for Classifying Performance Gestures in Music 20th

New Interfaces for Classifying Performance Gestures in Music

引用

20th international conference on intelligent data engineering and automated learning (IDEAL)

作者： Rhodes, Chris Allmendinger, Richard Climent, Ricardo Univ Manchester NOVARS Res Ctr Manchester Lancs England Univ Manchester AMBS Manchester Lancs England

ISBN: (纸本)9783030336172;9783030336165

Interactive machine learning (ML) allows a music performer to digitally represent musical actions (via gestural interfaces) and affect their musical output in real-time. Processing musical actions (termed performance gestures) with ML is useful because it predicts and maps often-complex biometric data. ML models can therefore be used to create novel interactions with musical systems, game-engines, and networked analogue devices. Wekinator is a free open-source software for ML (based on the Waikato Environment for Knowledge Analysis - WEKA - framework) which has been widely used, since 2009, to build supervised predictive models when developing real-time interactive systems. this is because it is accessible in its format (i.e. a graphical user interface - GUI) and simplified approach to ML. Significantly, it allows model training via gestural interfaces through demonstration. However, Wekinator offers the user several models to build predictive systems with. this paper explores which ML models (in Wekinator) are the most useful for predicting an output in the context of interactive music composition. We use two performance gestures for piano, with opposing datasets, to train available ML models, investigate compositional outcomes and frame the investigation. Our results show ML model choice is important for mapping performance gestures because of disparate mapping accuracies and behaviours found between all Wekinator ML models.

关键词： Interactive machine learning Wekinator Myo HCI Performance gestures Interactive music Gestural interfaces

来源：评论

学校读者我要写书评

暂无评论

Classical-Quantum Multiple Access Wiretap Channel with Common Message: One-Shot Rate Region

Classical-Quantum Multiple Access Wiretap Channel with Commo...

引用

conference on Information and Knowledge Technology

作者： Hadi Aghaee Bahareh Akhbari Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran

the following topics are dealt with: learning (artificial intelligence); graph theory; text analysis; neural nets; natural language processing; data mining; telecommunication security; statistical analysis; feature ex... 详细信息

ISBN: (数字)9781665404419

ISBN: (纸本)9781665404426

关键词： Decoding Quantum networks

来源：评论

学校读者我要写书评

暂无评论

Deep learning for Big data Time Series Forecasting Applied to Solar Power 13th

Deep Learning for Big Data Time Series Forecasting Applied t...

引用

Int Joint Conf of the 13th Int Conf on Soft Comp Models in Ind and Environm Applicat (SOCO) / 11th Int Conf on Computat Intelligence in Secur for Informat Syst (CISIS) / 9th Int Conf on European Transnat Educ (ICEUTE)

作者： Torres, J. F. Troncoso, A. Koprinska, I Wang, Z. Martinez-Alvarez, F. Univ Pablo de Olavide Div Comp Sci Seville 41013 Spain Univ Sydney Sch Informat Technol Sydney NSW Australia

ISBN: (纸本)9783319941202;9783319941196

Accurate solar energy prediction is required for the integration of solar power into the electricity grid, to ensure reliable electricity supply, while reducing pollution. In this paper we propose a new approach based on deep learning for the task of solar photovoltaic power forecasting for the next day. We firstly evaluate the performance of the proposed algorithm using Australian solar photovoltaic data for two years. Next, we compare its performance with two other advanced methods for forecasting recently published in the literature. In particular, a forecasting algorithm based on similarity of sequences of patterns and a neural network as a reference method for solar power forecasting. Finally, the suitability of all methods to deal with big data time series is analyzed by means of a scalability study, showing the deep learning promising results for accurate solar power forecasting.

关键词： Deep learning Big data Solar power Time series forecasting

来源：评论

学校读者我要写书评

暂无评论

A Convolutional Neural Network Based Ensemble Method for Cancer Prediction Using DNA Methylation data 19

A Convolutional Neural Network Based Ensemble Method for Can...

引用

11th international conference on Machine learning and Computing (ICMLC)

作者： Xia, Chao Xiao, Yawen Wu, Jun Zhao, Xiaodong Li, Hua Shanghai Jiao Tong Univ Sch Biomed Engn Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China East China Normal Univ Sch Life Sci Shanghai Peoples R China Shanghai Jiao Tong Univ Shanghai Ctr Syst Biomed Shanghai Peoples R China

ISBN: (纸本)9781450366007

Cancer is a deadly disease all over the world and its morbidity is increasing at an alarming rate in recent years. With the rapid development of computer science and machine learning technologies, computer-aid cancer prediction has achieved increasingly progress. DNA methylation, as an important epigenetic modification, plays a vital role in the formation and progression of cancer, and therefore can be used as a feature for cancer identification. In this study, we introduce a convolutional neural network based multi-model ensemble method for cancer prediction using DNA methylation data. We first choose five basic machine learning methods as the first stage classifiers and conduct prediction individually. then, a convolutional neural network is used to find the high-level features among the classifiers and gives a credible prediction result. Experimental results on three DNA methylation datasets of Lung Adenocarcinoma, Liver Hepatocellular Carcinoma and Kidney Clear Cell Carcinoma show the proposed ensemble method can uncover the intricate relationship among the classifiers automatically and achieve better performances.

关键词： DNA methylation convolutional neural network cancer prediction machine learning

来源：评论

学校读者我要写书评

暂无评论

An intelligent Diagnosis Method of Bearing Fault Based on Acoustic Signal Processing

An Intelligent Diagnosis Method of Bearing Fault Based on Ac...

引用

Prognostics and System Health Management (PHM-Jinan), international conference on

作者： Guowei Zhang Shanshan Ji Baokun Han Sixiang Jia College of mechanical and electronic engineering Shandong University of science and technology Qingdao China

ISBN: (数字)9781728151816

ISBN: (纸本)9781728151823

Acoustic signals are widespread applied in fault diagnosis. However, it is still a difficult problem to extract feature of acoustic signals under large rotation speed fluctuation. Sparse filtering (SF) as an effective unsupervised algorithm, has been skillfully applied in many fields. However, the effect of SF on acoustic signal processing under large rotation speed fluctuation is not ideal. Hence, we proposed an effective feature learning algorithm called deep sparse filtering (DSF) to overcome this teaser. Firstly, frequency domain signals are used as the basis of DSF for feature leaning, then weight adjustment is performed by back propagation (BP). the efficiency of the DSF model is verified by the collected bearing data set.

关键词： Acoustics Feature extraction Filtering Training Standards Fluctuations Fault diagnosis

来源：评论

学校读者我要写书评

暂无评论

Research Progress on Ship Anomaly Detection Based on Big data

Research Progress on Ship Anomaly Detection Based on Big Dat...

引用

IEEE international conference on Software engineering and Service Sciences (ICSESS)

作者： Bohan Zhang Hongxiang Ren Pengjie Wang Delong Wang Key Laboratory of Marine Dynamic Simulation Dalian Maritime University Dalian Liaoning Province China

ISBN: (数字)9781728165790

ISBN: (纸本)9781728165806

the purpose of ship behavior anomaly detection is to identify and monitor some non-expected behaviors of ships, so as to improve the navigation safety of ships. Its research is of great significance to the safety guarantee of maritime navigation, intelligent monitoring of sea areas and the development of port management. this paper summarizes and evaluates the research progress of ship anomaly detection based on big data and points out the future development trend. First of all, the concept of ship abnormal behavior is introduced, and the process of data-driven ship abnormal detection and its data basis are described in detail. Secondly, the data-driven ship anomaly detection methods are divided into statistical method, machine learning method and neural network method, and their research status and existing problems are reviewed respectively. Finally, focusing on maritime big data, temporal and spatial correlation of scenarios, online real-time anomaly detection and other aspects, the current problems and challenges in the study of ship anomaly detection are discussed, and the future research direction is introduced.

关键词： Statistical analysis Navigation Neural networks Big data Safety Marine vehicles Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Design of Question Answering System for Railway Electricity Accidents

Design of Question Answering System for Railway Electricity ...

引用

IEEE international conference on Software engineering and Service Sciences (ICSESS)

作者： Hanjiao Meng Xiaohong Wang Xuan Gao School of Information Science and Engineering Hebei University of Science and Technology Shijiazhuang China

ISBN: (数字)9781728165790

ISBN: (纸本)9781728165806

Based on multi-source data of railway electrical accident, an intelligent Q&A(question answering) system based on knowledge graph of railway electrical accident is realized in this paper, which can improve the intelligence and convenience of accident information retrieval. First of all, in order to complete the construction of the railway electrical accident knowledge graph, the conceptual structure design, knowledge extraction, and knowledge storage technology are used in this paper. In addition, the overall architecture of the railway electrical accident intelligent Q&A system is designed, and question preprocessing, question classification, and answer retrieval techniques are used to achieve the Q&A system. Finally, in order to achieve the functions and visualizations of Q&A system, this system is built based on Flask-framework, combining Echarts module, data tables and Neo4j-knowlegde-graph. therefore, correctness, scientificalness and visual effects are guaranteed.

关键词： data visualization Visual effects Knowledge discovery Rail transportation User experience Electrical accidents Software engineering

来源：评论

学校读者我要写书评

暂无评论

An EMD-based Method for the Detection of Power Transformer Faults with a Hierarchical Ensemble Classifier

An EMD-based Method for the Detection of Power Transformer F...

引用

international conference on Electrical and Computer engineering (ICECE)

作者： Shoaib Meraj Sami Mohammed Imamul Hassan Bhuiyan Bangladesh University of Engineering and Technology Dhaka Bangladesh

ISBN: (数字)9781665422543

ISBN: (纸本)9781665446617

In this paper, an Empirical Mode Decomposition-based method is proposed for the detection of transformer faults from Dissolve gas analysis (DGA) data. Ratio-based DGA parameters are ranked using their skewness. Optimal sets of intrinsic mode function coefficients are obtained from the ranked DGA parameters. A Hierarchical classification scheme employing XGBoost is presented for classifying the features to identify six different categories of transformer faults. Performance of the Proposed Method is studied for publicly available DGA data of 377 transformers. It is shown that the proposed method can yield more than 90% sensitivity and accuracy in the detection of transformer faults, a superior performance as compared to conventional methods as well as several existing machine learning-based techniques.

关键词： Fault diagnosis Sensitivity Empirical mode decomposition Machine learning Feature extraction Power transformers data mining

来源：评论

学校读者我要写书评

暂无评论

the Application of the Internet of things Technology in Apple Production 11

The Application of the Internet of Things Technology in Appl...

引用

11th IEEE international conference on Advanced Infocomm Technology, ICAIT 2019

作者： Wang, Zhijun Wang, Yucun Lan, Peng Sun, Fenggang Shandong Agricultural University College of Information Science and Engineering Tai'an China

ISBN: (纸本)9781728147789

To improve the yield and quality of apples, reduce the management cost in apple orchard, the introduction of the Internet of things (IOT) technology in fruit tree management can perceive every segment in fruit tree management and provide the basic data support. the IOT technology can help to monitor the environment information of apple orchards and the detailed data of apple growth, which is useful for management suggestion and planting decision. therefore, the application of IOT technology in apple orchard can make the apple tree management more scientific and intelligent. © 2019 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Towards improving incremental learning of manipulator kinematics with inter-robot knowledge transfer

Towards improving incremental learning of manipulator kinema...

引用

27th Southern African Universities Power engineering conference (SAUPEC) / 11th Robotics and Mechatronics conference of South Africa (RobMech) / 29th Annual Symposium of Pattern-Recognition-Association-of-South-Africa (PRASA)

作者： Makondo, Ndivhuwo Rosman, Benjamin CSIR Mobile Intelligent Autonomous Syst Pretoria South Africa Univ Witwatersrand Sch Comp Sci & Appl Math Johannesburg South Africa

ISBN: (纸本)9781728103693

this paper investigates the improvement of learning sensorimotor models for developmental robots, in particular robot arm kinematics models, with inter-robot knowledge transfer. Developmental robots progressively learn through embodied interaction with the physical environment. In the single-robot case, exploration in the world is performed in isolation and the robot explores its own capabilities. In a multi-robot case, with one or more experienced robots, we argue that it may be beneficial for the robots to be able to share the knowledge they have acquired through their individual exploration. We explore knowledge transfer in the context of learning arm kinematics models, where an experienced robot shares its kinematic data with a new robot that is autonomously exploring its environment We show that the sensorimotor models of the new robot can be bootstrapped by the shared knowledge, converge faster and also achieve a better asymptotic performance compared to individual exploration from scratch. We perform an analysis of knowledge transfer in simulation, ranging from simple two-link planar robots to redundant systems.

关键词： Model learning Transfer learning Robot kinematics Robot learning Developmental robots

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 << < 433 434 435 436 437 438 439 440 441 442 > >>

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：