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

7,036 篇 会议
48 篇 期刊文献
39 册 图书

馆藏范围

7,123 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4,891 篇 工学
- 4,084 篇 计算机科学与技术...
- 2,510 篇 软件工程
- 1,042 篇 信息与通信工程
- 787 篇 控制科学与工程
- 662 篇 生物工程
- 633 篇 电气工程
- 426 篇 生物医学工程（可授...
- 284 篇 交通运输工程
- 280 篇 机械工程
- 225 篇 仪器科学与技术
- 224 篇 安全科学与工程
- 206 篇 建筑学
- 195 篇 动力工程及工程热...
- 183 篇 光学工程
- 166 篇 化学工程与技术
- 154 篇 土木工程
1,888 篇 理学
- 1,059 篇 数学
- 717 篇 生物学
- 440 篇 统计学（可授理学、...
- 281 篇 物理学
- 253 篇 系统科学
- 140 篇 化学
1,142 篇 管理学
- 651 篇 管理科学与工程(可...
- 577 篇 图书情报与档案管...
- 313 篇 工商管理
406 篇 医学
- 352 篇 临床医学
- 295 篇 基础医学(可授医学...
- 188 篇 药学(可授医学、理...
242 篇 教育学
- 241 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

556 篇 machine learning
453 篇 deep learning
264 篇 training
253 篇 data mining
234 篇 data models
219 篇 feature extracti...
214 篇 accuracy
183 篇 support vector m...
178 篇 predictive model...
138 篇 neural networks
136 篇 machine learning...
130 篇 computational mo...
120 篇 reinforcement le...
107 篇 convolutional ne...
101 篇 real-time system...
92 篇 forecasting
90 篇 learning systems
90 篇 artificial intel...
88 篇 transfer learnin...
86 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...
8 篇 school of remote...
8 篇 school of inform...
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

6,939 篇 英文
173 篇 其他
14 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 7123 条记录，以下是4931-4940 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：

Multi Parameter Machine learning-Based Maternal Healthiness Classification System 11th

Multi Parameter Machine Learning-Based Maternal Healthiness ...

引用

11th international conference on Frontiers of intelligent Computing: theory and Applications, FICTA 2023

作者： Ettiyan, Rajkumar Geetha, V. Department of Computer Science and Engineering Puducherry Technological University Puducherry India Department of Information Technology Puducherry Technological University Puducherry India

ISBN: (纸本)9789819967018

During pregnancy is needed to identify any problems early and ensure maternal and foetal health and well-being. But most people are lived in rural areas so, lack of regular checkups at the starting time of pregnancy time. So, number of unexpected deaths count has increased during delivery. In this paper, a novel Maternal Monitoring System (MMS) has been proposed for monitoring pregnant women at home, that helps in monitoring the maternal and foetal health such as body temperature, foetal heart rate, blood pressure, respiration rate, foetal movement, PPG, and abdominal ECG. the input data from the MIT-BIH arrhythmia dataset are pre-processed by using Stationary Wavelet Transform (SWT) it remove unwanted noise in the signal. Denoised signals are decomposition using Variational Mode Decomposition (VMD) which is identify AECG signal into its constituent maternal and foetal components. After identify, the both signals are classified by using Support Vector Machine (SVM) it produces the best classification results, regardless of whether the maternal or foetal are healthy or unhealthy. According to the experimental findings, the proposed MMS model’s overall accuracy was 98.9%. the proposed MMS model was compared with other traditional models like KNN, MLE, and Navy Bayes obtains less accuracy compared to SVM. SVM maintains the high accuracy of 99%. the accuracy rate obtained by the SVM is more efficient than the existing model, respectively. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electrocardiograms

来源：评论

学校读者我要写书评

暂无评论

Abnormal Detection of Financial Fraud in Listed Companies Based on Deep learning 11

Abnormal Detection of Financial Fraud in Listed Companies Ba...

引用

11th international conference on Information Technology and Quantitative Management, ITQM 2024

作者： Li, Yunqi Fu, Boxin Tong, Yuxi Tang, Zhiying Shang, Zhidi Li, Aihua School of Management Science and Engineering Central University of Finance and Economics China

this study aims to improve the accuracy of detecting financial fraud in listed companies by applying various deep learning algorithms. First, we comprehensively reviewed the current state of research on financial fraud theory and identified 67 recognition features to create a new recognition indicator system. then, we collected data samples of all A-share listed companies from 2010 to 2022, preprocessed them, and generated a basic dataset. To address the unbalanced dataset, we used the Borderline-SMOTE algorithm. Empirical analysis results show that this algorithm can significantly improve the recognition performance of the model. Finally, we conducted experiments on the new dataset using three types of deep learning algorithms. the results show that the model constructed using the Long Short-Term Memory (LSTM) algorithm has the best prediction performance, with an accuracy rate higher than that of the DCRN, autoencoder, and other models. In addition, the classification effects of all deep learning algorithms are better than basic models and ensemble models. this research provides a powerful tool for the regulatory authorities of listed companies, helping them more effectively monitor and prevent financial fraud. We have three innovations in this study: (1) Development of a comprehensive recognition indicator system with 67 features;(2) Utilization of the Borderline-SMOTE algorithm to handle data imbalance;(3) Demonstration of the superior performance of the LSTM algorithm compared to other deep learning, basic, and ensemble models. © 2024 the Authors.

关键词： Contrastive learning

来源：评论

学校读者我要写书评

暂无评论

Hybrid classifiers for improved semantic subspace learning of news documents

Hybrid classifiers for improved semantic subspace learning o...

引用

international conference on Hybrid intelligent Systems (HIS)

作者： Nandita Tripathi Michael Oakes Stefan Wermter Department of Computing Engineering and Technology University of Sunderland Sunderland UK Institute for Knowledge Technology Department of Computer Science University of Hamburg Hamburg Germany

the volume and diversity of documents available in today's world is increasing daily. It is therefore difficult for a single classifier to efficiently handle multi-level categorization of such a varied document space. In this paper we analyse methods to enhance the efficiency of a single classifier for two-level classification by combining it with classifiers of other types. We use the maximum significance value as an indicator for the subspace of a test document. We represent the documents using the conditional significance vector which increases the distinction between classes within a subspace. Our experiments show that dividing a document space into different semantic subspaces increases the efficiency of such hybrid classifier combinations. Applying different types of classifiers on different subspaces substantially improves overall learning.

关键词： Vectors Support vector machine classification Semantics Accuracy Classification algorithms Training Niobium

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Machine learning Model for Predicting Customer Churn in the Telecommunication Industry 11th

A Hybrid Machine Learning Model for Predicting Customer Chur...

引用

11th international conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2020 and 10th World Congress on Information and Communication Technologies, WICT 2020

作者： Odusami, Modupe Abayomi-Alli, Olusola Misra, Sanjay Abayomi-Alli, Adebayo Sharma, Mayank Mohan Department of Electrical and Information Engineering Covenant University Ota Nigeria Department of Software Engineering Kaunas University of Technology Kaunas Lithuania Department of Computer Science Federal University of Agriculture Abeokuta Abeokuta Nigeria Zillow Inc San Francisco United States

ISBN: (纸本)9783030736026

the churn rate, being a major issue in the telecommunication industry today as it describes the degree at which customers desert a company and discard its services in one way or another. Over the past years, various changes evolved in the telecommunications industry like liberalization of the market, giving rise to serious competition and hence the evolution of new technologies and opportunities which directly and indirectly affect customer choice and preference for the services of a specific telecommunications company. In this study, a generalized K_LoRD hybrid model for predicting customer churn in the telecommunication industry was developed using K Nearest Neighbor, Logistic Regression, Random Forest and Decision Tree. A publicly available dataset from a telecom company which has a record of customer information and their churn was collected. the K_LoRD hybrid model is evaluated based on the following performance metrics: Accuracy and Receiver Operating Curve. the results showed that the hybrid model efficiently predicts customer churn with 91.85% prediction accuracy and 95.9% Area Under Curve. the experiments have shown that our hybrid prediction model is superior to ordinary K nearest Neighbor, Logistic Regression, Random Forest and Decision Trees. © 2021, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Advances in Computational Intelligence 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Joan Cabestany Ignacio Rojas Gonzalo Joya

ISBN: (数字)9783642214981

ISBN: (纸本)9783642214974

this two-volume set LNCS 6691 and 6692 constitutes the refereed proceedings of the 11th international Work-conference on Artificial Neural Networks, IWANN 2011, held in Torremolinos-Málaga, Spain, in June 2011. the 154 revised papers were carefully reviewed and selected from 202 submissions for presentation in two volumes. the second volume includes 76 papers organized in topical sections on video and image processing; hybrid artificial neural networks: models, algorithms and data; advances in machine learning for bioinformatics and computational biomedicine; biometric systems for human-machine interaction; data mining in biomedicine; bio-inspired combinatorial optimization; applying evolutionary computation and nature-inspired algorithms to formal methods; recent advances on fuzzy logic and soft computing applications; new advances in theory and applications of ICA-based algorithms; biological and bio-inspired dynamical systems; and interactive and cognitive environments. the last section contains 9 papers from the international Workshop on intelligent Systems for Context-Based Information Fusion, ISCIF 2011, held at IWANN 2011.

关键词： Computational Biology/Bioinformatics Pattern Recognition Artificial Intelligence data Mining and Knowledge Discovery Models and Principles Bioinformatics

来源：评论

学校读者我要写书评

暂无评论

Quantitative Analysis of Propagandistic Narratives in Large Text Corpses Using Machine learning Methods 11

Quantitative Analysis of Propagandistic Narratives in Large ...

引用

11th international Research conference Information Technology and Implementation - Workshop: intelligent Systems and Security, IT and I-WS 2024: ISS

作者： Dagil, Illia Vergunova, Iryna Tereshchenko, Yaroslav Taras Shevchenko National University of Kyiv Akademika Hlushkova Av. 4d Kyiv03680 Ukraine

this paper presents a novel algorithm for topic modeling, specifically designed to identify and analyze propaganda narratives in large-scale news corpora. the algorithm combines advanced natural language processing techniques, embedding models, and clustering algorithms to assist analysts, communication experts, and government agencies in efficiently processing and identifying propaganda content. A series of experiment was conducted on multiple datasets to throughly test the algorithm's performance. In these experiments, five different embedding models were compared along with four clustering algorithms, each tested with various hyperparameters. A significant challenge addressed was determining the appropriate granularity of clusters, balancing between detailed analysis and broader trends. Additionally, narrative extraction was deeply investigated using large language models (LLMs) providing accurate and structured identification of complex narratives. this approach allows not only the identification of propaganda but also the development of counter-narratives, with the potential to be adapted for broader applications such as communication network analysis. © 2024 Copyright for this paper by its authors.

关键词： Embeddings

来源：评论

学校读者我要写书评

暂无评论

An ensemble multivariate model for resource performance prediction in the cloud

An ensemble multivariate model for resource performance pred...

引用

11th IFIP WG 10.3 international conference on Network and Parallel Computing, NPC 2014

作者： Hirwa, Jean Steve Cao, Jian Shanghai Jiao Tong University Department of Computer Engineering 800 Dongchuan Road Minhang District Shanghai 200240 China

ISBN: (纸本)9783662449165

In cloud environment, multiple resources performance prediction is the task of predicting different resources by considering the differences from multiple task inferences based on the historical values to make effective and certainty judgmental decisions for the future values. One resource performance prediction can conclude the performance of another, which implies dependency (i.e., multi-resources) or independency (i.e., one resource), but that cannot be directly confirmed accurately. We use time series algorithms to investigate possible approaches, which can greatly assist us to analyze and predict the future values based on previously observed values. the goal of this paper is to review the theory of the common several models of multivariate time series, and to emphasize the practical steps to take in order to fit those models to real data and evaluate the outcome. Moreover, ensemble-learning algorithms are applied to the best-fit models to improve performance. Finally, we will discuss the results. © 2014 IFIP international Federation for Information Processing.

关键词： Time series

来源：评论

学校读者我要写书评

暂无评论

Scenarios to Handle Shifts data Pattern Using Neural Network for Forecasting Indonesian GDP Based on Financial Growth at Risk 11

Scenarios to Handle Shifts Data Pattern Using Neural Network...

引用

11th international conference on Electrical engineering, Computer Science and Informatics, EECSI 2024

作者： Saputra, Wisnowan Hendy Prastyo, Dedy Dwi Fithriasari, Kartika Institut Teknologi Sepuluh Nopember Department of Statistics Surabaya Indonesia

ISBN: (纸本)9798350355314

Modeling time series data through statistical techniques is a common practice in economics, primarily aimed at forecasting economic indicators such as GDP to prepare for future trends. Over time, statistical modeling has increasingly incorporated machine learning (ML) methods. Although ML offers flexibility in model equations, accurate projections still require that future data patterns align with historical ones, which is often not the case. this research examines the impact of changes or shifts in time series data patterns by exploring various scenarios for determining the length of training data used in modeling. As an empirical application, this study also provides a framework for projecting Indonesia's GDP by utilizing financial indicators such as the Financial Stress Index (FSI) as predictors. the model employed is QRNN-MIDAS, which accommodates differences in the frequency of responses variable (quarterly) and predictors (monthly) to estimate high-frequency financial Growth-at-Risk (GaR)-based on GDP growth, ultimately applied to forecast the actual GDP value. the analysis identifies the optimal scenario as one using a year-on-year GDP growth calculation with data limited to the period following a shift in the data pattern (from 2011 to 2023) and including a dummy predictor variable for the COVID-19 pandemic. According to this scenario, Indonesia's economic growth in 2024 is projected to be between 3.64% and 6%, with the GDP at constant 2010 prices ranging from 2.96 to 3.13 trillion rupiah. Assuming no unforeseen adverse events, Indonesia's economy in 2024 is expected to be stable and show a tendency to grow. © 2024 IEEE.

关键词： Inflation

来源：评论

学校读者我要写书评

暂无评论

Application of Laser Scanning to Capture Geospatial Information in Soil-Structure Interaction Studies of Instrumented Structures with Geotechnical Arrays 11

Application of Laser Scanning to Capture Geospatial Informat...

引用

11th international conference on Structural Health Monitoring of intelligent Infrastructure, SHMII 2022

作者： Takhirov, Shakhzod Orunbaev, Sagynbek Pilz, Marco Mendekeev, Raiymkul Shamansurov, Ravshan Department of Civil and Environmental Engineering University of California Berkeley 337 Davis Hall BerkeleyCA94720 United States Scientific-Research Institute of Seismic Construction State University of Constructions Transport and Architecture Bishkek Kyrgyzstan Helmholtz Center Potsdam German Research Center for Geosciences Helmholtzstr. 7 Potsdam14467 Germany Sigma Innovative Tech Tashkent Uzbekistan

Investigating soil-structure interaction problems require an extensive amount of information including material properties of the soil, relief of the ground surface, and locations of buildings, to name a few. Geospatial information is especially invaluable when there is a correlation to the actual performance of the buildings under measured excitations from nearby bore holes. this paper demonstrates an approach to addressing this problem of collecting geospatial data via the utilization of a laser scanner. A terrestrial laser scanner was used to collect the above ground geometry of instrumented structures studied together with a geotechnical array. the spatial locations of the array, the surrounding structures, and the relief features of the ground surface are captured by the laser scanner. the latter information is very important when the ground surface has a large slope or there are large deviations of the ground surface from the horizontal or even sloped surface. the advantages of this approach for structural health monitoring are discussed in a few examples and is scheduled to be utilized for a system in Kyrgyzstan consisting of a geotechnical array and a few instrumented buildings. Major features of the latter system are discussed in this paper.. © 2022 international conference on Structural Health Monitoring of intelligent Infrastructure: Transferring Research into Practice, SHMII. All rights reserved.

关键词： Soil structure interactions

来源：评论

学校读者我要写书评

暂无评论

Research and Practice of "Trinity" Construction of Emerging engineering Big data Course Teaching Quality Assurance System during the Epidemic

Research and Practice of "Trinity" Construction of Emerging ...

引用

Information and Education Technology (ICIET), international conference on

作者： Mingyou Liu Yingxue Zhu Li Li Yue Wang School of Biology and Engineering Guizhou Medical University Guizhou China

the pandemic of the COVID-19, has brought a great impact to the education and teaching, so the teaching can only be carried out online, in order to ensure the monitoring and management of teaching quality during teaching. this project import the latest information intelligent teaching system, multi-directional to ensure the monitoring and control of teaching quality, the deep integration of "Rain Classroom" technology and teaching in this project, So that the interaction information between teachers and students can be recorded in real time during the online teaching, and organized, analyzed, stored also; Import the online teaching platform, collected the students records that finished homework during the epidemic; Import the online virtual experiment platform, online to finished the remote experimental operation of students. thus, the trinity builds a three-dimensional teaching quality assurance system to escort high-quality big data course teaching during the epidemic.

关键词： COVID-19 Quality assurance Rain Distance learning Pandemics Education Big data

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 << < 490 491 492 493 494 495 496 497 498 499 > >>

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：