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

1,890 篇 会议
6 册 图书
1 篇 期刊文献

馆藏范围

1,897 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,395 篇 工学
- 1,275 篇 计算机科学与技术...
- 1,022 篇 软件工程
- 318 篇 生物工程
- 311 篇 信息与通信工程
- 190 篇 生物医学工程（可授...
- 162 篇 控制科学与工程
- 124 篇 电气工程
- 120 篇 光学工程
- 83 篇 机械工程
- 74 篇 化学工程与技术
- 65 篇 安全科学与工程
- 63 篇 网络空间安全
- 54 篇 电子科学与技术（可...
- 48 篇 仪器科学与技术
760 篇 理学
- 399 篇 数学
- 327 篇 生物学
- 173 篇 统计学（可授理学、...
- 152 篇 物理学
- 134 篇 系统科学
- 83 篇 化学
449 篇 管理学
- 253 篇 管理科学与工程(可...
- 232 篇 图书情报与档案管...
- 131 篇 工商管理
175 篇 医学
- 166 篇 临床医学
- 159 篇 基础医学(可授医学...
- 117 篇 药学(可授医学、理...
- 63 篇 公共卫生与预防医...
82 篇 教育学
- 82 篇 教育学
77 篇 法学
- 69 篇 社会学
52 篇 农学
- 51 篇 作物学
46 篇 经济学
4 篇 军事学

主题

325 篇 machine learning
135 篇 deep learning
78 篇 support vector m...
65 篇 machine learning...
55 篇 forecasting
46 篇 feature extracti...
37 篇 decision trees
35 篇 computational mo...
34 篇 accuracy
34 篇 computer vision
30 篇 predictive model...
29 篇 training
29 篇 convolutional ne...
28 篇 data mining
28 篇 students
26 篇 neural networks
22 篇 object detection
22 篇 artificial intel...
21 篇 sentiment analys...
20 篇 internet of thin...

机构

12 篇 chitkara univers...
7 篇 shenyang ligong ...
6 篇 uttaranchal inst...
5 篇 department of co...
5 篇 maharishi school...
5 篇 alibaba cloud bi...
4 篇 school of comput...
4 篇 college of compu...
4 篇 key laboratory o...
4 篇 lovely professio...
4 篇 jilin agricultur...
4 篇 uttaranchal univ...
4 篇 key laboratory o...
4 篇 department of co...
4 篇 master of comput...
4 篇 school of inform...
3 篇 school of comput...
3 篇 vivekananda glob...
3 篇 department of el...
3 篇 college of compu...

作者

4 篇 liu gang
4 篇 kumar rakesh
4 篇 waseemullah
4 篇 liu peng
3 篇 zhang tao
3 篇 kumar ajay
3 篇 rakesh kumar
3 篇 babu tina
3 篇 siddhant
3 篇 sharma arun
3 篇 faisal rehman
3 篇 wang xiaofei
3 篇 sharif hanan
3 篇 gupta rajeev kum...
3 篇 singh sunil kuma...
3 篇 rehman faisal
3 篇 tina babu
3 篇 yang wei
3 篇 sharma avinash
3 篇 prajwal

语言

1,776 篇 英文
119 篇 其他
18 篇 中文

检索条件"任意字段=3rd International Conference on Machine Learning and Computer Application, ICMLCA 2022"

共 1897 条记录，以下是821-830 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：

Dataset Classification Using Various machine learning Algorithms 3rd

Dataset Classification Using Various Machine Learning Algori...

引用

3rd international conference on machine learning, Advances in Computing, Renewable Energy and Communication, MARC 2021

作者： Nagpal, Muskaan Mishra, Richa Computer Science Department Amity University Uttar Pradesh Noida India

ISBN: (纸本)9789811928277

The extensively used CIFAR-10 dataset, which is commonly used to analyze image classification technique. The analysis of an efficient classification approach for the CIFAR10 dataset using a convolutional neural network, dense neural networks, and support vector machines is presented in the research. Convolutional neural network (CNN) model was enhanced with learnable filters, pooling, and padding layers, and the dataset was transformed into two dimensions for support vector machine (SVM) model using picture preprocessing in Python. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

machine learning-based Multilabel Toxic Comment Classification 3

Machine Learning-based Multilabel Toxic Comment Classificati...

引用

3rd IEEE international conference on Computing, Communication, and Intelligent Systems, ICCCIS 2022

作者： Singh, Nitin Kumar Chand, Satish Jawaharlal Nehru University School of Computer and Systems Sciences New Delhi India

ISBN: (纸本)9781665462006

The emergence of social media marked the beginning of a revolution not just in the realm of digitalization but also in that of communication. In spite of the fact that social media platforms make it possible for anyone located anywhere in the world to express their viewpoints and interact with a large audience, social media has also evolved into a venue for cruel behaviour, offensive language, cyberbullying, personal assaults, and the use of profane language. To tackle this challenge, we are detecting the toxicity level in the Jigsaw dataset by Google, which consists of six different classes, including toxic, severe_toxic, obscene, threat, insult, and identity_hate. This is a multilabel classification in which one comment can fall under more than one class. We study the impact of Multinomial NB, Logistic Regression, and Support Vector machine with TF-IDF on identifying toxicity in text. These models were trained using the training data and after training were tested on the test data provided in the dataset. Experimental results show that Logistic Regression trumps the other models in terms of accuracy and hamming loss. © 2022 IEEE.

关键词： Toxicity

来源：评论

学校读者我要写书评

暂无评论

IOT Based Clinical Data Set Formation Model for Smart Health Care application 3

IOT Based Clinical Data Set Formation Model for Smart Health...

引用

3rd international conference on Intelligent Engineering and Management, ICIEM 2022

作者： Shrivastava, Anurag Chauhan, Divyansh Negi, Prashansha Jain, Neha Chauhan, Hemant Singh, Sohan Sushila Devi Bansal College Indore India Chitkara University Department of Computer Science and Application Punjab Rajpura Chandigarh India Graphic Era Hill University Uttarakhand Dehradun India Galgotias University Department of Management Uttar Pradesh Noida India GRD College Uttarakhand Dehradun India

ISBN: (数字)9781665467568

ISBN: (纸本)9781665467568

The rapid development of the Internet and computer technology makes it possible to develop IoT based health care services in today's ageing population. However, the IoT data problem in elderly care seriously restricts the process of intelligentization in this field. Issues such as missing real IoT data, interference of dirty IoT data and too few standard samples emerge in an endless stream. Aiming at the problem of missing IoT data sets, based on collecting a small sample IoT data of community health care in a city, a three-stage IoT data generation model based on machine learning is proposed. The generation strategy based on tree structure is used in the first stage. The distribution of the IoT data generates the essential attributes of the IoT data set;in the second stage, the naive Bayesian algorithm is used to generate the primary behavioural ability evaluation index of the sample;in the third stage, the multiple linear regression method is used to generate the high Behavioral competency indicators and evaluation stages. In addition, to verify the effectiveness of the IoT data set generated by the model for downstream tasks, based on the generated IoT data, this paper uses neural networks to design multiple rehabilitation training plan recommendation models to achieve five multi-classification tasks and two multi-label classification tasks. Finally, this paper verifies the authenticity and validity of the generated IoT data by analyzing the experimental results and injecting expert knowledge. © 2022 IEEE.

关键词： Linear regression

来源：评论

学校读者我要写书评

暂无评论

Exploiting Knowledge Graph for Multi-faceted Conceptual Modelling using GCN 3

Exploiting Knowledge Graph for Multi-faceted Conceptual Mode...

引用

3rd international conference on Industry 4.0 and Smart Manufacturing (ISM)

作者： Wan, Yuwei Chen, Zhenyuan Hu, Fu Liu, Ying Packianather, Michael Wang, Rui Cardiff Univ Sch Engn Inst Mech & Mfg Engn Cardiff CF24 3AA Wales UNICMICRO Sci Town Commercial PlazaKexue Rd Guangzhou 510000 Peoples R China

The relevant information obtained from multiple sources usually contributes to one intricate phenomenon in the industrial processes. Data fusion of different sources usually leads to more expressive and informative information than that of each single data source. Integrated information has been widely used to model a multi-faceted conceptual phenomenon, which provides a comprehensive and versatile view of understanding of the process. However, the conventional approaches concatenate feature vectors to integrate different facets, not considering the semantic gaps between them. Meanwhile, knowledge graph (KG) receives considerable attention in recent years as it comprises rich relational information among elements. Thus, KG provides a promising way to fuse multiple data sources by bridging the semantic gaps, which can be exploited in the modelling of a multi-faceted phenomenon. Inspired by the advancement of KG, we proposed an approach based on KG and a machine learning algorithm for multi-faceted modelling. Firstly, a domain-specified ontology was built to eliminate the varying distance metrics across facet boundaries, and KGs were generated by populating the data surrounding a multi-faceted phenomenon into this ontology. Secondly, the KGs were fed into a graph convolutional neural network (GCN) to learn the node features and the graph structure for graph embedding simultaneously with the shared parameters. Lastly, with the aim of multi-faceted conceptual modelling, the features obtained from the GCN model were used as inputs for machine learning algorithms to learn the hidden patterns of KGs. An experimental study using real-world data from the cold rolling process was conducted to demonstrate the feasibility of the proposed model. (C) 2022 The Authors. Published by Elsevier B.V.

关键词： knowledge graph graph embeddings graph convolutional neural network multi-faceted data

来源：评论

学校读者我要写书评

暂无评论

6th Asia-Pacific Web and Web-Age Information Management international Joint conference on Web and Big Data, APWeb-WAIM 2022: 5th international Workshop on Knowledge Graph Management and applications, KGMA 2022, 4th international Workshop on Semi-structured Big Data Management and applications, SemiBDMA 2022, and 3rd international Workshop on Deep learning in Large-scale Unstructured Data Analytics, DeepLUDA 2022

6th Asia-Pacific Web and Web-Age Information Management Inte...

引用

6th Asia-Pacific Web and Web-Age Information Management international Joint conference on Web and Big Data, APWeb-WAIM 2022: 5th international Workshop on Knowledge Graph Management and applications, KGMA 2022, 4th international Workshop on Semi-structured Big Data Management and applications, SemiBDMA 2022, and 3rd international Workshop on Deep learning in Large-scale Unstructured Data Analytics, DeepLUDA 2022

ISBN: (纸本)9789819913534

The proceedings contain 24 papers. The special focus in this conference is on Asia-Pacific Web and Web-Age Information Management international Joint conference on Web and Big Data. The topics include: Analysis of Public Opinion Evolution in Public Health Emergencies Based on Multi-fusion Model;Failure Simulation Study of Double-Layer Exhaust Manifold for Turbocharged Engine Under LCF & HCF;lung Electrical Impedance Tomography Based on Improved Generative Adversarial Network;snake Robot Motion Planning Based on Improved Depth Deterministic Policy Gradient;Global Path Planning for Multi-objective UAV-Assisted Sensor Data Collection: A DRL Approach;Infrared Image Object Detection of Vehicle and Person Based on Improved YOLOv5;slow Port Scanning Attack Detection Algorithm Based on Dynamic Time Window Mechanism;AU-GAN: Attention U-Net Based on a Built-In Attention for Multi-domain Image-to-Image Translation;multi-robot Online Complete Coverage Based on Collaboration;effectively Filtering Images for Better Multi-modal Knowledge Graph;A Long Short-Term Urban Air Quality Prediction Model Based on Spatiotemporal Merged GLU and GCN;colour Coherence Entropy for Ceramic Fragment Analysis;a Fast Method of Legal Decision Recommendation System;an Encryption Key Sharing Method for Contact Tracing application;a Non-contact Interaction Method for 3D Display Devices;accelerating Distributed Knowledge Graph System Based on Non-Volatile Memory;towards a Unified Storage Scheme for Dual Data Models of Knowledge Graphs;cross-platform Product Matching Based on Knowledge Graph;A GCN-Based Sequential Recommendation Model for Heterogeneous Information Networks;SP-LAN: A Stock Prediction Model Based on LSTM-Attention Network;research on Composite Index Construction Method Based on Master-Slave Blockchain Structure;multi-source Heterogeneous Blockchain Data Quality Assessment Model.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Filter-Based learning Approach for Intrusion Detection using The NSL-KDD Network Dataset 3

A Filter-Based Learning Approach for Intrusion Detection usi...

引用

3rd international conference on Smart Electronics and Communication, ICOSEC 2022

作者： Madala, Chandu Jagan Sekhar Patil, Anita M Santhosh Srinivasan, P. Kousar, Heena Sultanuddin, Sj Sangeeth Kumar, M. Lendi Institute of Engineering & Technology Department of Computer Science & Engineering Andhra Pradesh Vizianagaram535005 India Bharati Vidyapeeth Yashawantrao Mohite Institute of Management Karad Department of Mca Maharashtra Malkapur415539 India Panimalar Engineering College Department of Mathematics Tamil Nadu Chennai600123 India East Point College of Engineering and Technology Department of Computer Science and Engineering Karnataka Bangalore560049 India Measi Institute of Information Technology Department of Mca Tamil Nadu Chennai600014 India Sona College of Technology Department of Mechanical Engineering Tamil Nadu Salem636005 India

ISBN: (数字)9781665497640

ISBN: (纸本)9781665497640

Wireless sensor network (WSN) attacks seek to disrupt or eliminate the network's ability to execute its expected duties. Penetration testing is a wireless sensor network defence that detects unknown threats. Because of the significant advancement in computer based products and widespread Internet utilization, it is critical to guarantee hosting and information systems. A hacking technique has been proposed to breach computer security with infiltration. An intrusion detection system (IDS) identifies network breaches with machine learning (ML) methods. Classic ML methods based feature extraction frequently resulted in low efficiency and misreading incursions. To address these challenges, this research provides a novel architecture for IDS that may be facilitated by the filter-based learning methodL The anticipated model performance is comparable to ML techniques. The appropriate solution was built and evaluated using network security laboratories - discovering dataset information (NSL-ICDD). The experimental data reveal that the suggested model filter-based learning detects assaults with more accuracy (i.e., 99 percent) than LDA, CART, and other current approaches. © 2022 IEEE.

关键词： Wireless sensor networks

来源：评论

学校读者我要写书评

暂无评论

AutoRoC-DBSCAN: Automatic Tuning of DBSCAN to Detect Malicious DNS Tunnels 3rd

AutoRoC-DBSCAN: Automatic Tuning of DBSCAN to Detect Malicio...

引用

3rd international conference on Emerging Information Security and applications (EISA)

作者： Nguyen, Thi Quynh Laborde, Romain Benzekri, Abdelmalek Oglaza, Arnaud Mounsif, Mehdi Univ Paul Sabatier F-31000 Toulouse France MODIS F-31300 Toulouse France

ISBN: (纸本)9783031230974;9783031230981

Domain Name System (DNS) is one of the core services of the Internet. Whereas it was created to associate domain names and IP addresses, modern attacks, such as Advanced Persistent Threats, use tunneling techniques over the DNS protocol to build covert channels in order to infiltrate the local network or exfiltrate data while bypassing security systems. Unsupervised machine learning techniques, and more specifically, Density-Based Spatial Clustering of applications with Noise (DBSCAN), can achieve good results in detecting simple malicious DNS tunnels. However, DBSCAN requires manually tuning two hyperparameters, whose optimal values can be different depending on the dataset. In this article, we propose an improved algorithm called AutoRoC-DBSCAN that can automatically find the best hyperparameters, in order to automate the detection of malicious DNS tunnels in a completely new dataset.

关键词： DNS tunneling APT Unsupervised machine learning DBSCAN

来源：评论

学校读者我要写书评

暂无评论

Auto-feature extraction for industrial machine learning based on system dynamics diagram 3

Auto-feature extraction for industrial machine learning base...

引用

3rd international conference on computer Science and Communication Technology, ICCSCT 2022

作者： Tian, Chunhua Yu, Chentao Wang, Chen Xie, Keqiang Beijing Innovation Center for Industrial Big Data Beijing100083 China Lenovo Research Beijing100085 China School of Software Tsinghua University Beijing100083 China China Electronic Product Reliability and Environmental Testing Research Institute Guangzhou511325 China

ISBN: (纸本)9781510661240

In industrial data analytics, many useful features are implicitly reflected in system connection and interaction. Manual feature extraction is tedious and low-efficiency. An automated feature extraction approach based on system dynamics diagram is proposed in this paper. System mechanism and control policy are captured by system dynamics diagram (SDG). Four typical SDG structures identification algorithms are introduced, including anchor variable, single path, parallel branch, and closed-loop. Feature extraction operators can be configured according to graph structures. The approach is illustrated with a feedwater flow control system. Such a formalized graph structure based automated machine learning can significantly reduce feature extraction efforts. © 2022 SPIE.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Two applications of machine learning on COVID-19 3

Two Applications of Machine Learning on COVID-19

引用

3rd international conference on Electronics and Communication;Network and computer Technology (ECNCT)

作者： Liu, Yeqian Tao, Xingyi Hu, Songjia Southwest Univ Chongqing Peoples R China North China Elect Power Univ Beijing Peoples R China Beijing Univ Civil Engn & Architecture Beijing Peoples R China

ISBN: (数字)9781510652118

ISBN: (纸本)9781510652118;9781510652101

In December 2019, a new virus called COVID-19 broke out, and in 2020, it rapidly spread all over the world. The fast rate of the spread of the virus and high mortality have brought severe harm to the health of people and the economy of almost all countries around the world. Therefore, the virus has become the object of much researches. As the study moving on, treatment and vaccine have become the leading research directions at present. For treatment, measures should be taken to protect the most severe patients to reduce the death rate, and thus we are supposed to find patients with more serious illnesses. The decision tree and Xgboost are used to get the mathematical model about protease (an essential index in judging the severity of the disease) and realize the visualization of protease data. For vaccine, we solve the problem of predicting COVID-19 Vaccination Progress in the world in 2021 using the ARIMA model, which is obtained through the mean of time-series. Eventually, we got 10-day and 3-month vaccination forecasts.

关键词： machine learning COVID-19 death rate

来源：评论

学校读者我要写书评

暂无评论

Vector angle-based and ISDE+ indicator selection for many-objective evolutionary optimization 3

Vector angle-based and ISDE+ indicator selection for many-ob...

引用

3rd international conference on Electronic Information Engineering, Big Data, and computer Technology, EIBDCT 2024

作者： Liu, Peng Chen, Hanning Liu, Keyi Wang, Guopeng Song, Lizhe Xia, Yelin Jia, Kun School of Computer Science and Technology Tiangong University Tianjin300387 China College of Artificial Intelligence Tianjin University of Science and Technology Tianjin300457 China School of Mechanical and Electrical Engineering Xinjiang Institute of Engineering Xinjiang Wulumuqi830023 China The Open University of China Beijing100039 China Engineering Research Center of Integration and Application of Digital Learning Technology Ministry of Education Beijing100039 China Jingwei Textile Machinery Beijing00176 China

ISBN: (纸本)9781510680449

Many-objective optimization problems are challenging for the majority of extant multi-objective evolutionary algorithms to solve because they are unable to strike a balance between diversity and convergence in the high-dimensional objective space. Therefore, for many-objective evolutionary optimization, this paper proposes a vector angle-based and ISDE+ indicator selection strategies. Using these two strategies, the worst individual are repeatedly removed from the population through environmental selection. More specially, the first one is aimed at finding any two individuals that have the smallest vector angle, which indicates that they are looking in the same research direction. The latter considers the individuals with poor convergence and diversity, which are eliminated according to the value of ISDE+ indicator one by one. Experimental results revel that the proposed algorithm obtains competitive advantages on various benchmark problems with up to 10 objectives, when the proposed algorithm is compared with several state-of-the-art many-objective algorithms. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Vectors

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190页 << < 79 80 81 82 83 84 85 86 87 88 > >>

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：