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

256 篇 会议
3 篇 期刊文献
2 册 图书

馆藏范围

261 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

196 篇 工学
- 183 篇 计算机科学与技术...
- 123 篇 软件工程
- 37 篇 信息与通信工程
- 35 篇 生物工程
- 25 篇 生物医学工程（可授...
- 19 篇 电气工程
- 15 篇 机械工程
- 8 篇 控制科学与工程
- 7 篇 光学工程
- 7 篇 化学工程与技术
- 7 篇 交通运输工程
- 5 篇 动力工程及工程热...
- 5 篇 电子科学与技术（可...
- 4 篇 仪器科学与技术
- 4 篇 土木工程
71 篇 理学
- 40 篇 数学
- 35 篇 生物学
- 18 篇 统计学（可授理学、...
- 14 篇 系统科学
- 11 篇 物理学
- 7 篇 化学
50 篇 管理学
- 34 篇 管理科学与工程(可...
- 23 篇 图书情报与档案管...
- 22 篇 工商管理
18 篇 医学
- 12 篇 基础医学(可授医学...
- 11 篇 临床医学
- 8 篇 药学(可授医学、理...
8 篇 法学
- 7 篇 社会学
7 篇 经济学
- 7 篇 应用经济学
5 篇 教育学
- 5 篇 教育学
3 篇 农学

主题

71 篇 machine learning
17 篇 deep learning
14 篇 data analytics
13 篇 machine learning...
10 篇 predictive model...
9 篇 big data
8 篇 support vector m...
8 篇 predictive analy...
8 篇 decision trees
8 篇 artificial intel...
7 篇 data mining
6 篇 classification
5 篇 covid-19
5 篇 real-time system...
5 篇 prediction algor...
5 篇 data visualizati...
5 篇 accuracy
5 篇 forecasting
4 篇 clustering
4 篇 self-supervised ...

机构

3 篇 university of du...
2 篇 ecloud system an...
2 篇 amity school of ...
2 篇 department of ar...
2 篇 aset amity unive...
2 篇 department of co...
2 篇 banasthali vidya...
2 篇 meghnad saha ins...
2 篇 department of el...
2 篇 department of co...
2 篇 bba in marketing...
2 篇 vardhaman colleg...
2 篇 shanghai jiao to...
2 篇 study group aust...
2 篇 zhejiang lab peo...
2 篇 college of manag...
2 篇 department of el...
2 篇 information syst...
2 篇 autonomous unive...
2 篇 college of infor...

作者

2 篇 fatima ruhi
2 篇 v. karthik
2 篇 j. sasidevi
2 篇 du siyu
2 篇 ma yong
2 篇 ferreira joao c.
2 篇 zhao yong
2 篇 zhang sichao
2 篇 tong jinyu
2 篇 chen yu
2 篇 draschner carste...
2 篇 wathiq mansoor
2 篇 m. a. jabbar
2 篇 kazi sabeena
2 篇 zhao shouwang
2 篇 galpin ixent
2 篇 suryanarayana g.
2 篇 pan haiyang
2 篇 lehmann jens
2 篇 shahbaz nadeem

语言

255 篇 英文
6 篇 其他
1 篇 中文

检索条件"任意字段=5th International Conference on Applied Machine Learning and Data Analytics, AMLDA 2022"

共 261 条记录，以下是231-240 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：

Carbohydrate Recommendation for Type-1 Diabetics Patient Using machine learning

Carbohydrate Recommendation for Type-1 Diabetics Patient Usi...

引用

international conference on Contemporary Computing and Informatics (IC3I)

作者： S V N Sreenivasu Sakshi Gupta Ghanshyam Vatsa Anurag Shrivastava Swati Vashisht Aparna Srivastava Department of Computer Science and Engineering Narasaraopeta Engineering College Narasaraopet Andhra Pradesh India Department of Professional Communication Graphic Era Deemed to be University Dehradun Uttarakhand India Department of Swasthavritta & Yog G S Ayurveda Medical College & Hospital Pilkhuwa Hapur Uttar Pradesh Saveetha School of Engineering Saveetha Institute of Medical and Technical sciences Chennai Tamilnadu Amity University Greater Noida Uttar Pradesh India Department of MCA Lloyd Institute of Engineering and Technology Greater Noida Uttar radesh India

Diabetes is a chronic illness that develops when the blood glucose level is elevated above normal. Diabetes has a variety of reasons, making diagnosis and treatment more difficult than necessary. A patient’s treatment can benefit greatly from a healthy diet. It is important to keep the diet under control so that it doesn’t include an excessive amount of carbohydrates. this study offers assistance in this case by creating a mobile application and website that can suggest a meal item based on the patient’s needs. For this construction, a dataset with basic data about more than fifty different food items is taken from Kaggle. this dataset is then preprocessed utilizingstandardization and encoding methods. To create two machine learning (ML)models, two different ML algorithms were applied. In this study, the K Nearest Neighbor (KNN) and Naïve Bayes (NB) algorithms were used. the models are subsequently trained using the preprocessed dataset. the models are also put to the test to see which one forecasts the patient’s ideal food item the most accurately. the NBalgorithm is the best method that may be used for carbohydrate recommendation, according to the testing of these models. this model’s accuracy is 93.12%.the model is therefore installed in the firebase. Another database that contains the patient’s real-time readings is linked to the firebase software as well. the best meal item with the right amount of carbohydrates is then given by the doctor through the website. A food proposal is provided to the patient’s mobile phone together with information like the values of the vital metrics. Based on the patient’s vital signs and required carbohydrate intake, the ML system particularly selects this meal item.

关键词： machine learning algorithms Software algorithms Medical services Predictive models Prediction algorithms Software Real-time systems

来源：评论

学校读者我要写书评

暂无评论

A novel approach for high-velocity big geo-data handling using iterative and feature learning algorithms 5

A novel approach for high-velocity big geo-data handling usi...

引用

5th international conference on Fog and Mobile Edge Computing (FMEC)

作者： Rekik, Sana Faiz, Sami Higher Inst Management Tunis LTSIRS Lab Natl Engineers Sch Tunis Tunis Tunisia Higher Inst Multimedia Art Manouba LTSIRS Lab Natl Engineers Sch Tunis Tunis Tunisia

ISBN: (纸本)9781728172163

Geospatial data were exclusively generated by official agencies. However, following the technological revolution in data collection and production, various sources have emerged for the massive production of geospatial data, resulting the phenomenon of big geo-data. therefore, dealing with large amounts of these data sets, results in a high velocity as they change very quickly, is a challenging task. Hence, analysis become more complex and computation become prohibitively expensive. As a result, spatial computing technologies become limited in front of these complex data and operations. Accordingly, we aimed to refine complexity with simplicity by replacing traditional geospatial models with referring to the simplest intelligent and minimum resource requirement algorithms that can be applied against these constraints, while ensuring the criteria of performance and scalability. In this work, we focus on the high-velocity of this big geo-data through the use of an iterative approach applied to a feature learning algorithms to decrease the memory consumption and the time complexity of traditional machine learning algorithms. According to our knowledge, although they were widely applied in the 19th century as a solution to overcome the problems of limitation of memory and computing resources. Iterative methods were still not used for the big geo-data analytics and generally for the big data domain. thus, this approach could be beneficial especially for real time applications such as the anomaly monitoring and detection.

关键词： Big geo-data analysis High-velocity data Iterative approach Feature learning algorithms Anomaly monitoring and detection

来源：评论

学校读者我要写书评

暂无评论

A Survey on Deep learning and machine learning for COVID-19 Detection 2021

A Survey on Deep Learning and Machine Learning for COVID-19 ...

引用

the 5th international conference on Future Networks & Distributed Systems

作者： Mohamed M. Dessouky Sahar F. Sabbeh Boushra Alshehri University of Jeddah Saudi Arabia

ISBN: (纸本)9781450387347

Coronaviruses are a type of virus that can cause a variety of disorders and exist in different types. COVID-19 is derived from a special type of a respiratory illness caused by the SARS-CoV-2 virus, discovered in 2019. Approximately two years ago, COVID-19 was discovered in the Chinese city of Wuhan, and it has since become a worldwide source of concern. A COVID-19 confirmed patient is experiencing symptoms such as fever, fatigue, and a dry cough. Based on the results of laboratory tests and/or chest X-rays, the COVID-19 diagnosis is established. When it comes to research using chest CT scans /X-ray for the diagnosis of COVID-19, which is based on medical imaging, Artificial Intelligence (AI) approaches are increasingly being applied in a variety of ways. machine learning and deep learning are fields of artificial intelligence that can be used to analyze the data that was acquired in order to better understand the origins of COVID-19. the outcomes of applying such an approach will aid in a better understanding of the nature of the threat and how it might be mitigated. For this reason, this work gives an overview of deep learning and machine learning approaches for the detection of COVID-19. Several COVID-19 detection methods are discussed in detail, as well as the issues, current challenges associated with artificial intelligence and medical researchers' approaches to providing a comprehensive assessment of detecting COVID-19.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Regression Algorithm Based on Self-Distillation and Ensemble learning 2021

Regression Algorithm Based on Self-Distillation and Ensemble...

引用

2021 5th international conference on Computer Science and Artificial Intelligence

作者： Yaqi Li Qiwen Dong Gang Liu School of Data Science&Engineering East China Normal University China China Academy of Launch Vehicle Technology China

ISBN: (纸本)9781450384155

Low-dimensional feature regression is a common problem in various disciplines, such as chemistry, kinetics, and medicine, etc. Most common solutions are based on machine learning, but as deep learning evolves, there is room for performance improvements. A few researchers have proposed deep learning-based solutions such as ResidualNet, GrowNet and EnsembleNet. the latter two methods are both boost methods, which are more suitable for shallow network, and the model performance is basically determined by the first model, with limited effect of subsequent boosting steps. We propose a method based on self-distillation and bagging, which selects the well-performing base model and distills several student models by appropriate regression distillation algorithm. Finally, the output of these student models is averaged as the final result. this integration method can be applied to any form of network. the method achieves good results in the CASP dataset, and the R2(Coefficient of Determination) of the model is improved from (0.65) to (0.70) in comparison with the best base model ResidualNet.

关键词： Knowledge distillation Regression Deep learning Ensemble learning

来源：评论

学校读者我要写书评

暂无评论

Predictive analysis of the supply chain management using machine learning approaches: Review and Taxonomy 5

Predictive analysis of the supply chain management using Mac...

引用

5th IEEE international conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2020

作者： Pham, Xuan Vy Maag, Angelika Senthilananthan, Sunthatalingam Bhuiyan, Moshiur Study Group Australia Sydney Australia ECloud System and Consulting

ISBN: (纸本)9781728194370

Currently, there are many literature reviews on the application of predictive analytics in Supply Chain Management (SCM). However, most of them focus only on some specific functions in supply chain management, including Procurement, Demand Management, Logistics and Transportation, or purely technical aspects. the purpose of this paper is twofold: first, it aims to provide an overview of the outstanding supply chain management functions (SCMF) that apply predictive analytics;and second, to highlight practical approaches, algorithms, or models in SCM via a comparative review of machine learning approach for aspect-based predictive analysis. For these purposes, details of relevant literature were gathered and reviewed. Accordingly, this article will present the data, algorithms, and models applied in predictive analytics along with its performance, SCM result taxonomy, which includes all the necessary components in the effective implementing of SCMF. Via the result of the recent related publications and papers (2018- 2020), Demand management and Procurement are the two main areas of SCM, in which predictive analytics is often applied. Particularly, accurate demand forecasting and sensing (Demand management) and sourcing risk management and supplier selection (Procurement) are among the foremost applications of BDA-enabled predictive models. this taxonomy not only helps scientists to have a steppingstone to provide more valuable articles in the future but also allows manufacturers to gain an in-depth understanding of these elaborate scenarios and better manage the supply chain management functions (SCMF) via the application of predictive analytics. © 2020 IEEE.

关键词： Supply chain management

来源：评论

学校读者我要写书评

暂无评论

iMobilAkou: the Role of machine Listening to Detect Vehicle using Sound Acoustics 21

iMobilAkou: The Role of Machine Listening to Detect Vehicle ...

引用

Proceedings of the 5th international conference on Advances in Artificial Intelligence

作者： Muddsair Sharif Mayur Hotwani Huseyin Seker Gero Luckemeyer informatics University of Applied Sciences Germany Faculty of Computing Engineering and the Built Environment Birmingham City University UK

ISBN: (纸本)9781450390699

machine learning can work very well with image recognition, but it is used to recognize audio patterns. machine listening identifies audio patterns of different entities like the car engine, human speaking, nature sounds, etc. the environmental sound classification plays an important role to encourage citizens to travel smartly within a city without creating unbearable noises. On the other hand, it also promotes the city council to maintain and predict a sustainable sound at rush hour with ins the city. the aim of this early-stage research is to present a methodology that will read the labeled audio files, extract features from them, feed features to a sequential model. Moreover, the model will have the ability to classify these audio files of vehicles based on their input feature(s) and then further categorize them as it either light-weight, medium-weight, heavy-weight, rail-bound or two-wheeled vehicle using the applications of machine listening and deep learning in the field of sound acoustics. therefore, It will also classify unlabelled test data files on a pre-trained model. this research provides us the base model for the vehicle classification giving both advantages and disadvantages along with the possibility for future extensions.

关键词： Intelligent Personal Assistants (IPA) deep learning (DL) M4LAB Environmental sounds classification (ESC) Message Passing Interface (MPI) Sound Acoustic(SA) machine Listening (ML) Intelligent Mobility using Sound Acoustic (iMobilAkou)

来源：评论

学校读者我要写书评

暂无评论

Expression of Concern for: Emotion Identification and Detection from Multichannel EEG Signals Using Artificial Neural Network

Expression of Concern for: Emotion Identification and Detect...

引用

international conference on Contemporary Computing and Informatics (IC3I)

作者： Cuddapah Anitha John E P K. Kathiresan N.J Krishnakumar. V. Karthik J. Sasidevi Department of Computer Science and Engineering Sree Vidyaniketan Engineering College Mohan Babu University Sri Sainath Nagar A Rangampeta Tirupati College of Management SRM Institute of Science and Technology Chennai TamilNadu India Department of Artificial Intelligence and Data Science KPR Institute of Engineering and Technology Coimbatore TamilNadu India Department of Electronics and Communication Engineering Gopalan College of Engineering and Management Seetharamapalaya Basava Nagar Bangalore Department of Electronics and Communication Engineering Sri Krishna College of Engineering and Technology Coimbatore TamilNadu India Department of Computer Science and Engineering K.Ramakrishnan College of Engineering Samayapuram Trichy TamilNadu

ISBN: (数字)9798350398267

ISBN: (纸本)9798350398274

Modified steady inclination affirmation considering multi-station EEG signals is shaping into a basic PC upheld technique for feeling issue finding in sensory system science and psychiatry as a problematic model affirmation task. In light of expansive space data, standard machine learning approaches call for arranging and eliminating various features from a lone or various channels. Along these lines, these strategies could acquaint a test with individuals who need point dominance. then again, huge learning frameworks have been truly applied in various persistent created endeavors to see consolidates and sort different kinds of information. In this overview, standard signals are considered, and a direct yet strong pre-managing methodology is proposed to expand confirmation accuracy. In the interim, by truly learning compositional spatial-standard depiction of unpalatable EEG streams, a cross mix brain network that joins "Convolution Brain Organization (CNN)" and "Long Brain Organization (RNN)" has been used to portray human tendency states. the CNN module changes the chain-like EEG gathering into a 2D packaging improvement to mine the between channel relationship among genuinely lining EEG ***, harshness, and wrath are several the various sentiments that people experience reliably. Electroencephalography (EEG) data should in this way have a convincing inclination recognizing confirmation structure to unequivocally reflect feeling. in the present. In spite of the way that new assessment on this issue can offer great execution estimations, they are at this point lacking for the execution of a full inclination affirmation system.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Microservice Based Architecture Topology for machine learning Deployment 5

A Microservice Based Architecture Topology for Machine Learn...

引用

5th IEEE Annual international Smart Cities conference (ISC2)

作者： Ribeiro, Jose Lucas Figueredo, Mickael Araujo, Adelson Cacho, Nelio Lopes, Frederico Univ Fed Rio Grande do Norte Dept Informat & Appl Math Natal RN Brazil

ISBN: (纸本)9781728108469

Smart solutions that make use of machine learning and data analyses are on the rise. Big data analysis is attracting more and more developers and researchers, and at least five requirements (Velocity, Volume, Value, Variety, and Veracity) show challenges in deploying such solutions. Across the globe, many Smart City initiatives are using Big data analytics as a tool for doing predictive analytics which can be helpful to human well being. this work presents a generic architecture named machine learning in Microservices Architecture (MLMA) that provides design patterns to transform a monolithic architecture of machine learning pipelines in microservices with separate roles. We present two case studies deployed to a Smart City initiative, where we discuss how each component of the architecture applied in specific applications that use predictions with machine learning. Among the benefits of this architecture, we argue prediction performance, scalability, code maintenance and reusability makes such transition a natural trend in Big data and machine learning applications.

关键词： microservices machine learning design patterns recommendation systems predictive policing

来源：评论

学校读者我要写书评

暂无评论

Game theoretical Approach for Non-Overlapping Community Detection 5

Game Theoretical Approach for Non-Overlapping Community Dete...

引用

5th international conference on Big data Computing and Communications (BIGCOM)

作者： Sun, Baohua Al-Bayaty, Richard Huang, Qiuyuan Wu, Dapeng Univ Florida Dept Elect & Comp Engn Gainesville FL 32611 USA

ISBN: (纸本)9781728140247

Graph clustering, i.e., partitioning nodes or data points into non-overlapping clusters, can be beneficial in a large varieties of computer vision and machine learning applications. However, main graph clustering schemes such as spectral clustering cannot be applied to a large network due to prohibitive computational complexity required. While there exist methods applicable to large networks, these methods do not offer convincing comparisons against known ground truth. For the first time, this work conducts clustering algorithm performance evaluations on large networks (consisting of one million nodes) with ground truth information. Ideas and concepts from game theory are applied towards graph clustering to formulate a new proposed algorithm, Game theoretical Approach for Clustering (GTAC). this theoretical framework is shown to be a generalization of both the Label Propagation and Louvain methods, offering an additional means of derivation and analysis. GTAC introduces a tuning parameter which allows variable algorithm performance in accordance with application needs. Experimentation shows that these GTAC algorithms offer scalability and tunability towards big data applications.

关键词： Big data analytics Game theory Clustering Community Detection Label Propagation

来源：评论

学校读者我要写书评

暂无评论

Predictive analysis of the supply chain management using machine learning approaches: Review and Taxonomy

Predictive analysis of the supply chain management using Mac...

引用

IEEE conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA)

作者： Xuan Vy Pham Angelika Maag Sunthatalingam Senthilananthan Moshiur Bhuiyan Study Group Australia Sydney Australia ECloud System and Consulting

ISBN: (数字)9781728194370

ISBN: (纸本)9781728194387

Currently, there are many literature reviews on the application of predictive analytics in Supply Chain Management (SCM). However, most of them focus only on some specific functions in supply chain management, including Procurement, Demand Management, Logistics and Transportation, or purely technical aspects. the purpose of this paper is twofold: first, it aims to provide an overview of the outstanding supply chain management functions (SCMF) that apply predictive analytics; and second, to highlight practical approaches, algorithms, or models in SCM via a comparative review of machine learning approach for aspect-based predictive analysis. For these purposes, details of relevant literature were gathered and reviewed. Accordingly, this article will present the data, algorithms, and models applied in predictive analytics along with its performance, SCM result taxonomy, which includes all the necessary components in the effective implementing of SCMF. Via the result of the recent related publications and papers (2018- 2020), Demand management and Procurement are the two main areas of SCM, in which predictive analytics is often applied. Particularly, accurate demand forecasting and sensing (Demand management) and sourcing risk management and supplier selection (Procurement) are among the foremost applications of BDA-enabled predictive models. this taxonomy not only helps scientists to have a steppingstone to provide more valuable articles in the future but also allows manufacturers to gain an in-depth understanding of these elaborate scenarios and better manage the supply chain management functions (SCMF) via the application of predictive analytics.

关键词： Procurement machine learning algorithms Taxonomy machine learning Predictive models Prediction algorithms Predictive analytics

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27页 << < 18 19 20 21 22 23 24 25 26 27 > >>

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：