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

1,325 篇 会议
27 册 图书
7 篇 期刊文献

馆藏范围

1,359 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

973 篇 工学
- 918 篇 计算机科学与技术...
- 635 篇 软件工程
- 236 篇 信息与通信工程
- 131 篇 控制科学与工程
- 101 篇 生物工程
- 97 篇 电气工程
- 64 篇 安全科学与工程
- 60 篇 动力工程及工程热...
- 58 篇 交通运输工程
- 58 篇 网络空间安全
- 47 篇 机械工程
- 47 篇 生物医学工程（可授...
- 42 篇 仪器科学与技术
- 29 篇 建筑学
- 28 篇 环境科学与工程（可...
354 篇 理学
- 183 篇 数学
- 113 篇 生物学
- 74 篇 统计学（可授理学、...
- 58 篇 化学
- 41 篇 物理学
- 31 篇 系统科学
347 篇 管理学
- 237 篇 管理科学与工程(可...
- 213 篇 图书情报与档案管...
- 121 篇 工商管理
62 篇 法学
- 52 篇 社会学
61 篇 医学
- 54 篇 临床医学
- 50 篇 基础医学(可授医学...
- 32 篇 药学(可授医学、理...
47 篇 经济学
- 47 篇 应用经济学
28 篇 教育学
- 28 篇 教育学
14 篇 农学
7 篇 文学
2 篇 军事学

主题

256 篇 big data
79 篇 artificial intel...
67 篇 cloud computing
63 篇 machine learning
50 篇 computational mo...
49 篇 deep learning
42 篇 internet of thin...
41 篇 data models
35 篇 training
27 篇 data mining
25 篇 neural networks
24 篇 smart cities
23 篇 predictive model...
23 篇 edge computing
21 篇 computational in...
21 篇 feature extracti...
19 篇 industries
18 篇 object detection
17 篇 social networkin...
16 篇 data privacy

机构

14 篇 ajou univ dept a...
13 篇 school of big da...
12 篇 renmin univ chin...
11 篇 beijing key lab ...
9 篇 college of compu...
7 篇 university of ch...
7 篇 beijing universi...
6 篇 school of comput...
6 篇 key laboratory o...
6 篇 school of comput...
6 篇 key laboratory o...
6 篇 shandong fundame...
5 篇 college of big d...
5 篇 national enginee...
5 篇 shiga university...
5 篇 ajou univ dept i...
5 篇 riken center for...
5 篇 gaoling school o...
5 篇 chongqing univ s...
5 篇 college of intel...

作者

13 篇 shin hyunjung
10 篇 liu yong
7 篇 geng xin
6 篇 zhou xiaokang
6 篇 dai fei
6 篇 mariano vladimir...
6 篇 li shaojie
6 篇 wang jun
5 篇 xu ning
5 篇 wang xiaofei
5 篇 li xiuhua
5 篇 yang yang
5 篇 su bing
5 篇 kim myungjun
5 篇 zhao wei
5 篇 qi jinli
5 篇 wu yanmin
5 篇 jin hai
5 篇 gao yanxia
5 篇 liu yiwen

语言

1,331 篇 英文
21 篇 其他
9 篇 中文
1 篇 西班牙文

检索条件"任意字段=International Conference on Big Data Intelligence and Computing, DataCom 2022"

共 1359 条记录，以下是271-280 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：

Training Echo-State Networks for big data Prediction using Variation of Parameters 16

Training Echo-State Networks for Big Data Prediction using V...

引用

16th international conference on Signal-Image Technology and Internet-Based Systems (SITIS)

作者： Seddik, Soukaina Routaib, Hayat El Haddadi, Anass Abdelmalek Essaadi Univ Data Sci & Competit Intelligence Team Appl Sci Lab LSA ENSAH Al Hoceima Morocco

ISBN: (纸本)9781665464956

Recurring neural networks (RNNs) are a class of neural networks that are naturally suitable for processing time series and other sequential data. RNNs and specifically Reservoir computing (RC) has attracted much attention over the past decade, particularly in the context of time series prediction. However, most time series have a multi-scale structure. The Echo State Networks (ESN) are one of two pioneering methods of reservoir computing. ESN requires some experiences and insights to achieve the acclaimed accuracy in many tasks. In this paper, we present a practical application of case prediction using several time series data, multiple parameters of our ESN system are scaled to compare the accuracy of the proposed model.

关键词： Reservoir computing Echo State Network RNN big data Analytics

来源：评论

学校读者我要写书评

暂无评论

Bayesian Ensembled Knowledge Extraction Strategy for Online Portfolio Selection

Bayesian Ensembled Knowledge Extraction Strategy for Online ...

引用

2022 IEEE international conference on big data, big data 2022

作者： Kumar, Abhishek Segev, Aviv University of Oulu Center for Ubiquitous Computing Oulu Finland University of Helsinki Department of Computer Science Helsinki Finland University of South Alabama Department of Computer Science Mobile United States

ISBN: (纸本)9781665480451

Online portfolio selection, one of the major fundamental problems in finance, has been explored quite extensively in recent years by machine learning and artificial intelligence communities. Recent state-of-the-art methods have focused on Mean Reversion significantly and have demonstrated outstanding performance. Another version of the same phenomenon, Median Reversion, has also performed well and demonstrated its ability to be robust against noises and outliers. Another important characteristic is Momentum. In this paper, a Bayesian ensembling approach to extract knowledge from both Mean Reversion and Median Reversion simultaneously based on the momentum associated with each one is proposed for the online portfolio selection task. The proposed method demonstrates its effectiveness by outperforming current state-of-the-art algorithms on several datasets. © 2022 IEEE.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Problems and Countermeasures in the Construction of Intelligent Government Under the Background of big data 18th

Problems and Countermeasures in the Construction of Intellig...

引用

18th international conference on Intelligent computing (ICIC)

作者： Pei, ZhaoBin Wang, Ying Dalian Ocean Univ Coll Marine Law & Humanities Dalian 116023 Peoples R China

ISBN: (纸本)9783031138324;9783031138317

With the rapid development of new generation of information technologies such as big data, cloud computing and the Internet of Things, the traditional government governance model has been unable to effectively cope with the changing social environment and new challenges. The development of big data has made significant progress and breakthroughs in government's modern governance ability, which has become a new path of government data governance. The construction of smart government and the realization of smart government governance model are based on the rule of law as the basic guarantee, big data and other science and technology as the basic conditions, and smart decision-making as the core to build a dynamic network collaborative governance mechanism among government, market and society, so as to realize the efficient governance mode of smart government and promote the modernization of government governance ability. Starting from the construction of smart government, this paper mainly analyzes the mode concept, challenges and countermeasures of smart government construction in the era of big data.

关键词： data sharing Smart cities Rule of law government

来源：评论

学校读者我要写书评

暂无评论

data mining for risk prediction of diabetes mellitus

Data mining for risk prediction of diabetes mellitus

引用

2022 international conference on Artificial intelligence, Information Processing and Cloud computing, AIIPCC 2022

作者： Li, Fulin Meng, Chen Wang, Cheng Fan, Shuyi Shijiazhuang Campus Army Engineering University Shijiazhuang China

ISBN: (纸本)9781665462877

Diabetes mellitus seriously affects human health. It is necessary to reasonably estimate the risk of diabetes and treat it as early as possible. With the rapid development of information technology and the application of big data, people have acquired a large number of medical data. Making good use of data resources is helpful to the analysis and prediction of diseases. In this paper, data mining technology is applied to the analysis of medical data, and association rules that can reflect the relationship between diseases and various factors are extracted from the data to provide support for early diabetes risk prediction. The disadvantages of classical Apriori algorithm are analysed and an improved algorithm is proposed. The experimental results show that the proposed method is effective. © 2022 IEEE.

关键词： data mining

来源：评论

学校读者我要写书评

暂无评论

Lightweight Model Inference on Resource-Constrained computing Nodes in Intelligent Surveillance Systems 6th

Lightweight Model Inference on Resource-Constrained Computin...

引用

6th Asia Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint international conference on Web and big data (APWeb-WAIM)

作者： Wang, Zhuohang Zhao, Yunfeng Wang, Yong Yan, Li Liu, Zhicheng Qiu, Chao Wang, Xiaofei Hu, Qinghua Tianjin Univ Coll Intelligence & Comp Tianjin Peoples R China State Grid Shandong Elect Power Co Informat & Telecommun Co Jinan Shandong Peoples R China

ISBN: (纸本)9783031251573;9783031251580

Intelligent Surveillance System (ISS) is an important application combining deep learning with IoT technologies. Meanwhile, multiple targets multiple camera tracking (MTMCT) has been widely recognized as a promising solution for ISS. However, current terminal devices have limited memory, power and computing power. Deep learning models deployed on these resource-constrained devices need to maintain a low-level number of parameters while ensuring inference delay and accuracy as much as possible. In this paper, we propose a lightweight model inference approach for resource-constrained edge computing nodes, which leverages the limited computing capability of edge devices for collaborative processing of model inference tasks. We consider a system model that includes a combination of both horizontal and vertical methods to dynamically partition deep neural networks. Further, we propose an adaptive strategy that dynamically controls the execution part in the terminal devices. In addition, a learning-based algorithm is used to obtain the near-optimal solutions for dynamic resource allocation decisions. Finally, we evaluate the system in terms of two metrics, i.e., computational latency and network throughput, based on a real-world dataset of campus surveillance. The experimental results reveal the superior effectiveness of the proposed scheme.

关键词： Lightweight model inference Edge intelligence Intelligent surveillance system Multiple targets multiple tracking Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

AR IN VR: AUGMENTED REALITY CUES IN 360-DEGREE STEREOSCOPIC TELEPRESENCE FOR REMOTE COLLABORATION AND MAINTENANCE 16

AR IN VR: AUGMENTED REALITY CUES IN 360-DEGREE STEREOSCOPIC ...

引用

16th international conference on Computer Graphics, Visualization, Computer Vision and Image Processing, CGVCVIP 2022, 8th international conference on Connected Smart Cities, CSC 2022, 7th international conference on big data Analytics, data Mining and Computational intelligence, bigDaCI 2022, and 11th international conference on Theory and Practice in Modern computing, TPMC 2022 - Held at the 16th Multi conference on Computer Science and Information Systems, MCCSIS 2022

作者： Kaynar, Furkan Hofbauer, Markus MacWilliams, Asa Newman, Joseph Hutter, Andreas Steinbach, Eckehard Media Technology Munich Institute of Robotics and Machine Intelligence Technical University of Munich Germany Siemens Technology Munich Germany

ISBN: (纸本)9789898704429

Remote maintenance and collaboration applications are getting more interest with the development of mixed reality technologies. The combination of 360-degree telepresence and augmented reality (AR) cues have been shown to be an effective way of remote collaboration. However, most existing methods do not provide depth perception which can improve the remote inspection. Also, many methods that use holograms for live collaboration are limited with only pointing functionality. In this paper, we present a 360-degree telepresence system interacting with an AR backend to create an immersive mixed reality interface for remote collaboration. The proposed camera system does not need to be carried by any on-site person, but can be controlled by the remote operator intuitively. We deploy network delay compensation methods and propose novel projection strategies for a correct and efficient rendering. A comparative analysis shows advantages of the proposed system over previous work and that it is a promising approach for improving remote collaboration and maintenance. © MCCSIS *** rights reserved.

关键词： Augmented reality

来源：评论

学校读者我要写书评

暂无评论

A K-Means Clustering Algorithm for data Analysis of Wearable Equipment of Construction Personnel 1

A K-Means Clustering Algorithm for Data Analysis of Wearable...

引用

1st IEEE international conference on Applied intelligence and Sustainable computing, ICAISC 2023

作者： Feng, Xinyue Luo, Xiaofeng Wen, Tianquan Yao, Jialu School of Electronic Information Foshan Polytechnic Guangdong Foshan China

ISBN: (纸本)9798350323795

Wearable device data analysis is the key to construction personnel management. In the process of wearable device data analysis, signal interruption is easy to occur, which reduces the accuracy of analysis, and causes key data loss and abnormal signal interference. This paper proposes a k-means clustering method to analyze the similarity of wearable device data, enhance the transmitted signals and shorten the interval between adjacent signals. Then, the signal attenuation and frequency are analyzed iteratively. Finally, the wearable device signals are searched by clustering theory, and the final analysis results are output. MATLAB shows that k-means clustering method can analyze data accurately, the data loss rate is less than 10%, and the analysis accuracy rate is more than 80%, which is better than single clustering analysis method. Moreover, in the k-means clustering method, the data analysis time of wearable devices is shorter, the location analysis time is 1/2, 1/4, and 1/6, and the abnormal signal recognition time in individual devices, group devices, and all devices are better than the single clustering method. Therefore, k-means clustering method can meet the data analysis requirements, and is suitable for construction personnel management. © 2023 IEEE.

关键词： Iterative methods

来源：评论

学校读者我要写书评

暂无评论

Application of big data in Intelligent Government Affairs Management: An Example in Natural Resources Management 7

Application of Big Data in Intelligent Government Affairs Ma...

引用

7th international conference on big data Analytics, ICBDA 2022

作者： Meng, Fanrong Yao, Min Kong, Dengkui Wang, Xuefei Fan, Yanping Meng, Fanjun Information Center of Ministry of Natural Resources Beijing China Academy of the National Territorial Planning Heilongjiang China

ISBN: (纸本)9781665479387

China's government affairs service has been rapidly evolving from the stage of data-guided to data-driven in recent years. The effective utilization of big data is a critical step toward developing a smart government affairs management system. Using natural resources big data as an example, this paper discusses the data architecture, spatial data analysis techniques and their applicability to intelligent land management system on a broad scale, as well as several technical challenges that must be addressed, such as integrated computing of multi-source distributed data, the lack of intelligence in the present government affairs management system, and the need for real-Time collaboration between multi-level databases. This paper intends to broaden researchers' understanding of big data technology and application in the field of natural resources, and it serves as a reference point for big data in the pursuit of intelligent government affairs management. © 2022 IEEE.

关键词： big data

来源：评论

学校读者我要写书评

暂无评论

Study on The Importance of Computer big data to Volleyball Match: Taking the data Analysis and Application of Women's Volleyball Video Challenge of 2020 Tokyo Olympics as an example 2

Study on The Importance of Computer Big Data to Volleyball M...

引用

2nd international conference on Statistics, Applied Mathematics, and computing Science, CSAMCS 2022

作者： Liu, Chenxi Ding, Yi Wang, Jun Faculty for Physical Education Shanghai International Studies University Shanghai China Faculty for Physical Education Fudan University Shanghai China

ISBN: (纸本)9781510663183

The Video Challenge System (VCS) was officially introduced at the 2016 Rio Olympics. Utilizing multiple on-site officiating tracking cameras and processing the captured images with back-end computers, this system was proven to provide fair and effective resolution for disputes. This paper adopts the following research methods: VCS review, and statistical analysis of data from the Women's Volleyball competition at the 2020 Tokyo Olympics. The author obtained the following results. Limited simulation of flight trajectory when a volleyball is in a close range to the net and limited amount of available data to generalize research findings. According to the Fédération internationale de Volleyball (FIVB), the most common challenges include touch, ball in/out, followed by faulty antennae. 1) VCS can produce accurate and transparent results and help minimize human judgment errors in the court owing to its extremely high prediction accuracy, and it can create an instant, objective, and direct 3D animation. 2) Mass data collection is required;the VCS analysis and application in the competition need further improvement. 3) The digitalization and intelligence process in the sports industry are facilitated through the interactions between Hawk-eye technology innovation and volleyball rules. 4) Greater granularity in volleyball sport development is stimulated by creating new challenges for athletes, coaches, and referees. © 2023 SPIE.

关键词： big data

来源：评论

学校读者我要写书评

暂无评论

A Multi-granularity Network for Time Series Forecasting on Multivariate Time Series data

A Multi-granularity Network for Time Series Forecasting on M...

引用

international Joint conference on Rough Sets (IJCRS)

作者： Wang, Zongqiang Xian, Yan Wang, Guoyin Yu, Hong Chongqing Univ Posts & Telecommun Chongqing Key Lab Computat Intelligence Chongqing Peoples R China Chongqing Univ Posts & Telecommun Key Lab Cyberspace Big Data Intelligent Secur Minist Educ Chongqing Peoples R China

ISBN: (纸本)9783031509582;9783031509599

Multivariate time series forecasting is a significant research problem in many fields, such as economics, finance, and transportation. The main challenge faced by current time series forecasting models is effectively capturing the information embedded in different temporal patterns. However, most existing methods analyze forecasting at a single time granularity. To alleviate this issue, we propose a novel approach called the multi-granularity hierarchical temporal forecasting network (MGTNet), which integrates three temporal convolution kernels based on the principles of granular computing. Specifically, the data from fine-grained, meso-grained, and coarse-grained are processed, respectively. Then, temporal dependence and variable dependence analyses are performed at different levels according to distinct granularities. Finally, they are stacked to form a complete multi-granularity network. The experimental results demonstrate that the proposed MGTNet outperforms a bunch of compared methods in terms of RSE, CORR on Traffic, Electricity and Solar-Energy datasets.

关键词： Multi-granularity Granular computing Hierarchy network Multivariate time series

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136页 << < 24 25 26 27 28 29 30 31 32 33 > >>

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：