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

6,837 篇 会议
70 篇 期刊文献
44 册 图书

馆藏范围

6,952 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

3,943 篇 工学
- 3,644 篇 计算机科学与技术...
- 2,747 篇 软件工程
- 1,195 篇 信息与通信工程
- 706 篇 控制科学与工程
- 511 篇 电气工程
- 472 篇 生物工程
- 333 篇 网络空间安全
- 312 篇 生物医学工程（可授...
- 275 篇 电子科学与技术（可...
- 261 篇 动力工程及工程热...
- 216 篇 交通运输工程
- 216 篇 安全科学与工程
- 210 篇 机械工程
- 210 篇 仪器科学与技术
- 179 篇 光学工程
- 167 篇 化学工程与技术
- 166 篇 石油与天然气工程
1,718 篇 理学
- 1,019 篇 数学
- 492 篇 生物学
- 369 篇 统计学（可授理学、...
- 305 篇 物理学
- 255 篇 化学
- 194 篇 系统科学
1,361 篇 管理学
- 776 篇 图书情报与档案管...
- 744 篇 管理科学与工程(可...
- 353 篇 工商管理
339 篇 医学
- 270 篇 临床医学
- 261 篇 基础医学(可授医学...
- 169 篇 公共卫生与预防医...
- 164 篇 药学(可授医学、理...
195 篇 法学
129 篇 经济学
87 篇 农学
69 篇 教育学
19 篇 文学
8 篇 军事学
2 篇 艺术学

主题

311 篇 big data
294 篇 machine learning
211 篇 deep learning
210 篇 data mining
202 篇 data models
158 篇 cloud computing
139 篇 machine learning...
124 篇 training
119 篇 computational mo...
116 篇 feature extracti...
108 篇 signal processin...
102 篇 predictive model...
98 篇 internet of thin...
96 篇 signal processin...
94 篇 prediction algor...
88 篇 support vector m...
83 篇 data privacy
80 篇 artificial intel...
74 篇 sentiment analys...
72 篇 edge computing

机构

88 篇 maharishi school...
67 篇 centre of interd...
31 篇 department of ar...
28 篇 tianjin universi...
28 篇 college of compu...
27 篇 vishwakarma inst...
26 篇 department of co...
26 篇 department of el...
25 篇 chitkara univers...
25 篇 department of co...
22 篇 department of in...
20 篇 vivekananda glob...
18 篇 university of ch...
18 篇 vishwakarma inst...
17 篇 chitkara univers...
17 篇 lovely professio...
17 篇 department of sc...
16 篇 department of el...
15 篇 vishwakarma inst...
14 篇 key laboratory o...

作者

13 篇 ramakrishnan ram...
11 篇 dipannita mondal
10 篇 wang jing
10 篇 nitin n. sakhare
10 篇 mondal dipannita
10 篇 rajeswari d.
9 篇 jambi ratna raja...
8 篇 kumar ritesh
8 篇 akhilendra prata...
8 篇 xu xiaolong
8 篇 li zuoyong
7 篇 chen chen
7 篇 liu ying
7 篇 wang tao
7 篇 vaishali singh
7 篇 kodipalli ashwin...
7 篇 zhang jing
6 篇 zheng-guang wu
6 篇 bin wang
6 篇 ye jun

语言

6,664 篇 英文
279 篇 其他
62 篇 中文
1 篇 西班牙文
1 篇 葡萄牙文

检索条件"任意字段=2023 International Conference on Algorithms, Computing and Data Processing, ACDP 2023"

共 6952 条记录，以下是401-410 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：

Research on Intelligent Analysis and processing System of Financial Big data Based on Machine Learning 5

Research on Intelligent Analysis and Processing System of Fi...

引用

5th international conference on Machine Learning, Big data and Business Intelligence, MLBDBI 2023

作者： Zhang, Yanhui Shandong Institute of Commerce and Technology Jinan Shandong China

ISBN: (纸本)9798350359930

The aim of this paper is to investigate a machine learning-based intelligent analysis and processing system for financial big data. With the fast growth of financial data, traditional methods of financial analysis are no longer suitable for handling and analyzing large-scale data. Hence, leveraging machine learning techniques for financial big data analysis has become an important trend. This paper firstly introduces the background and importance of financial big data. Next, it elaborates on the machine learning-based clustering algorithms for financial big data analysis, including machine learning algorithms, neural network algorithms, and K-means clustering algorithm. Then, the paper discusses the design of a machine learning-based financial big data platform management system, including the design of the platform's original data collection and analysis system and the design of the platform's intelligent operation and maintenance system. Lastly, through simulation experiments, the paper demonstrates the system's performance and provides an analysis of the results. With this research, intelligent analysis and processing of financial big data can be effectively achieved, providing scientific basis for financial decision-making. © 2023 IEEE.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

PCS-ADS: Privacy computing System for Agricultural data Security 24

PCS-ADS: Privacy Computing System for Agricultural Data Secu...

引用

8th international conference on Control Engineering and Artificial Intelligence, CCEAI 2024

作者： Wei, Zizhong Li, Rui Jiang, Kai Luo, Qingcai Sun, Zongchen Han, Tao Bi, Zixiang Wang, Yang Key Laboratory of Agricultural Blockchain Application Ministry of Agriculture and Rural Affairs Beijing China Inspur Academy of Science and Technology Shandong Jinan China

ISBN: (纸本)9798400707971

With the wide application of Internet of Things, big data and other technologies in smart agriculture, more and more agricultural data are collected and used. The current analysis and processing through IoT platforms and other centralised methods have more serious data security problems. Privacy computing is a technology that completes data security calculations under the premise that both parties do not disclose data, and the data of each participant participates in the calculation is in the form of cipher text to maximally reduce the risk of data leakage. Aiming at the small volume and high frequency scenario of agricultural data, this paper proposes a distributed privacy computing framework by integrating cryptography, edge computing and blockchain, and designs a privacy computing system called PCS-ADS for smart agricultural data. This paper focuses on describing the system model architecture and system function implementation, which includes key business processes, core modules, core algorithms and other parts. Finally, the security and performance evaluation of the system is carried out. The results show that, for sum and variance, the computation time for multi-party under the amount of 1w data of each party is no more than 0.1s, and for the high-frequency computation scenarios, the computation time under the amount of 100 data of each party is no more than 7s and 1.5s, respectively. Experimental results prove that PCS-ADS is effective and has a strong practicality. © 2024 ACM.

关键词： Agriculture

来源：评论

学校读者我要写书评

暂无评论

Research on risk assessment method of road risk grade assessment 8

Research on risk assessment method of road risk grade assess...

引用

8th international conference on Intelligent computing and Signal processing, ICSP 2023

作者： Pu, Shaoxin Chang'an Dublin International College of Transportation Chang'an University Xi'an China

ISBN: (纸本)9798350302455

This article studies big data technology, analyzes the relationship between various factors of urban road traffic and the occurrence of traffic accidents, and establishes a prediction model based on this. By collecting and processing a large amount of traffic data, including traffic flow, speed, weather, and other information, and combining historical traffic accident records, a prediction model based on machine learning was constructed. The model can monitor road traffic conditions in real time and predict the probability of traffic accidents. In addition, we have also verified and evaluated the model, proving its accuracy and practicality. This research contributes to improving the efficiency of traffic management and road safety, and has important practical significance. © 2023 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

BigHeuFIM: A Heuristic Apriori Algorithm for Extraction of Frequent Itemsets on Big data 3

BigHeuFIM: A Heuristic Apriori Algorithm for Extraction of F...

引用

3rd international conference on Innovative Sustainable Computational Technologies, CISCT 2023

作者： Sharma, Anu Srivastava, Atul Kumar Tripathi, Aditya Kumar Pandey, Neeraj Kumar Mishra, Amit Kumar Computer Science and Engineering Teerthanker Mahaveer University Moradabad India Amity University Department of IT and Engineering Tashkent Uzbekistan School of Computing DIT University Dehradun India Graphic Era Hill University Department of Computer Science & Engineering Dehradun India

ISBN: (纸本)9798350303360

The association rule mining is the method to mine the patterns associated with the data in transactions. Setting the minimum support to a lower value increases space complexity particularly when the dataset is sizable. There are various methods that struggle to scale because of their high time complexity or memory requirements. This situation arises need for approximate results in contrast to accurate results. This work proposes a divide-and-conquer approach based heuristic strategy, BigHeuFIM, that exponentially reduce time and space complexity. The experiments demonstrates that the BigHeuFIM significantly outperformed existing algorithms in terms of speed by processing items in 80% lesser time. © 2023 IEEE.

关键词： Association rules

来源：评论

学校读者我要写书评

暂无评论

Research and Applications of RBF Big data processing Technology Based on Artificial Intelligence algorithms

Research and Applications of RBF Big Data Processing Technol...

引用

2023 international conference on data Science and Network Security, ICDSNS 2023

作者： Duan, Xueying Wang, Meng Jilin Police College Department of Information Engineering Changchun China Hebei Public Security Vocational College Department of Technology and Tactics Shijiazhuang China

ISBN: (纸本)9798350301595

Among the processing technologies of big data, the most widely and deeply applied technology is prediction technology. The accuracy of predictions has important guiding significance for scientific decision-making. RBF neural networks have the advantages of simple structure, fast training speed, and strong approximation ability. The self-adaptability of its structure effectively avoids the limitation of initial weights. This article is based on artificial intelligence algorithms and optimizes the RBF neural network to obtain a more accurate prediction model. We will apply the improved RBF big data processing technology to the prediction of express delivery business volume. We have selected improved RBF big data processing technology and RBF big data processing technology to simultaneously predict the delivery volume of the business. Practice has shown that the improved RBF big data processing technology has higher prediction accuracy and lower mean square error. This article provides a reference for the improvement and innovation of RBF big data processing technology. © 2023 IEEE.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

Predicting User Perception Regarding Usefulness of Google Classroom Through Machine Learning algorithms 14

Predicting User Perception Regarding Usefulness of Google Cl...

引用

14th international conference on computing Communication and Networking Technologies, ICCCNT 2023

作者： Khan, Emran Akter, Afroza Prity, Sabrina Sultana Ur Rahman, Fahim Daffodil International University Department of English Dhaka Bangladesh Daffodil International University Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350335095

To investigate the attitudes of the students at the tertiary level of different institutes towards using google classroom as a convenient online platform for learning the English Language, especially contemplating reading and writing skills have been performed. A survey had been conducted including 448 EFL students at the tertiary level in Bangladesh from four different institutes to figure out the result of this research. data collection through a series of questionnaires had been posited based on learning reading and writing skills of the English Language. Finally, analyzing the data using machine learning algorithms, we concluded that google classroom is useful and effective in terms of learning the English language by elevating reading and writing skills of the students in Bangladesh based on the overall findings of both the survey and analyzing the data. Students' positive responses had been found towards using google classroom through this study. © 2023 IEEE.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Experimental Verification of Massive data Transfer for Super Intelligent computing Service

Experimental Verification of Massive Data Transfer for Super...

引用

IEEE/CIC international conference on Communications in China (ICCC)

作者： Han, Mengyao Liu, Ying Pang, Ran Zhang, Naihan Cao, Chang Tang, Xiongyan Huang, Tao China Unicom Res Inst Beijing Peoples R China Natl Engn Res Ctr Next Generat Internet Broadband Beijing Peoples R China China United Network Commun Grp Corp Ltd Beijing Peoples R China Beijing Univ Posts & Telecommun Beijing Peoples R China

ISBN: (纸本)9798350377675;9798350377682

With the development of super intelligent computing services, the requirement for massive data transfer (MDT) across long distance networks from edge data centers/enterprises to core data centers continues to increase. The network operators are strongly demanded to provide high efficiency MDT between the large-scales super intelligent computing centers. However, the conventional MDT scheme are achieved by manual express, which the valuable data suffer from security and damage risks. In this paper, we propose a low cost and highly efficient MDT scheme based on TCP for existing IP networks. To maximize the MDT rate and network bandwidth utilization, the TCP parameters are optimized. The performance of two congestion control algorithms, such as cubic and bbr, are studied in our experiment. The field experiments are also demonstrated to verify the MDT performance. The experiential results show that up to 9.18 Gbit/s MDT rate is achieved in a 1400 km field experiment with a 10 Gbit/s link rate. Moreover, it is worth noting that the proposed MDT scheme presents lower cost, higher efficiency, and flexibility for new supercomputing and intelligent computing services.

关键词： Super Intelligent computing Massive data transfer computing Power Network

来源：评论

学校读者我要写书评

暂无评论

Detecting Flood in Real-Time Weather data Using Anomaly Detection Algorithm 4

Detecting Flood in Real-Time Weather Data Using Anomaly Dete...

引用

4th international conference on Artificial Intelligence and data Sciences, AiDAS 2023

作者： Basheer, Muhammad Yunus Iqbal Ali, Azliza Mohd Hamid, Nurzeatul Hamimah Abdul Osman, Rozianawaty Nordin, Sharifalillah Ariffin, Muhammad Azizi Mohd College of Computing Informatics and Mathematics Universiti Teknologi Mara Selangor Shah Alam Malaysia

ISBN: (纸本)9798350318432

This paper presents flood detection using anomaly detection algorithms in real-time weather data. Nine different attributes are used to detect suspicious weather that can cause floods. The weather dataset was acquired from Kelantan, Malaysia. In this paper, the collected dataset will be sent from the chosen Internet of Things (IoT) pipeline to three different anomaly detection algorithms. These algorithms are multi-threaded autonomous anomaly detection (MAAD), robust random cut forest (RRCF), and outlier detection in feature-evolving data streams (xStream). Our evaluation demonstrates that the MAAD algorithm has a 68.5% precision score and a 0.01 false alarm rate, which is better than the RRCF and xStream for detecting floods. © 2023 IEEE.

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

An Innovation Development of Routing for Smart data Traffic Environment in data Mining 2

An Innovation Development of Routing for Smart Data Traffic ...

引用

2nd IEEE international conference on Distributed computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Ramachandran, T. Arvind, K.S. Department of Mechanical Engineering Bangalore India Bangalore India

ISBN: (纸本)9798350347456

The routing for smart data traffic environment in data mining is a complex process that requires advanced algorithms to allow for efficient data collection and analysis. The process starts with the initial data collection, which involves gathering data from various sources, such as sensors, web applications, and databases. Once the data is collected, it is processed and stored in a data warehouse. This data warehouse is then analyzed to identify patterns, correlations, and anomalies in the data. From there, algorithms are used to determine the optimal route for data traffic, based on factors such as distance, time, cost, and the likelihood of successful data transfer. The routing process involves both traditional and newer methods. Traditional methods include the use of routing tables, which allow for the efficient routing of data traffic to specific nodes in a network. Other methods include the use of route optimization algorithms, which take into account the traffic loads of different nodes in a network and prioritize the routing of data traffic in an optimal manner. Newer methods of routing data traffic include Software-Defined Networking (SDN), which is a software-based approach to routing data traffic. This approach allows for the use of automated routing algorithms that can quickly adjust the routing of data traffic based on the current traffic load. © 2023 IEEE.

关键词： data mining

来源：评论

学校读者我要写书评

暂无评论

Importance of Web Scraping as a data Source for Machine Learning algorithms - Review 17

Importance of Web Scraping as a Data Source for Machine Lear...

引用

17th IEEE international conference on Industrial and Information Systems, ICIIS 2023

作者： Sirisuriya, Scm De S General Sir John Kotelawala Defence University Department of Computer Science Faculty of Computing Sri Lanka

ISBN: (纸本)9798350323634

Machine learning is a branch of artificial intelligence (AI) that trains a machine to think as humans. Machine learning algorithms need large amounts of data for high-value predictions which helps to get better decisions in real-time environment with minimal human intervention. Machine Learning inherently requires data, but collecting data is very tedious and time-consuming task. Web Scraping is the technique which aims to address this issue. Web scraping or web data extraction used for extracting unstructured data from websites and transform into structured data and stored in a central local database or spreadsheet for future retrieval or analysis. In this review, we discuss the importance of web scraping as a data source for machine learning algorithms. © 2023 IEEE.

关键词： data mining

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 << < 37 38 39 40 41 42 43 44 45 46 > >>

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：