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

7,072 篇 会议
48 篇 期刊文献
39 册 图书

馆藏范围

7,159 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4,920 篇 工学
- 4,107 篇 计算机科学与技术...
- 2,511 篇 软件工程
- 1,065 篇 信息与通信工程
- 791 篇 控制科学与工程
- 662 篇 生物工程
- 657 篇 电气工程
- 423 篇 生物医学工程（可授...
- 286 篇 交通运输工程
- 283 篇 机械工程
- 226 篇 仪器科学与技术
- 226 篇 安全科学与工程
- 205 篇 建筑学
- 199 篇 动力工程及工程热...
- 184 篇 光学工程
- 168 篇 化学工程与技术
- 153 篇 土木工程
1,914 篇 理学
- 1,080 篇 数学
- 717 篇 生物学
- 441 篇 统计学（可授理学、...
- 284 篇 物理学
- 252 篇 系统科学
- 141 篇 化学
1,147 篇 管理学
- 655 篇 管理科学与工程(可...
- 578 篇 图书情报与档案管...
- 314 篇 工商管理
405 篇 医学
- 351 篇 临床医学
- 295 篇 基础医学(可授医学...
- 188 篇 药学(可授医学、理...
244 篇 教育学
- 243 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

557 篇 machine learning
458 篇 deep learning
262 篇 training
254 篇 data mining
235 篇 data models
220 篇 feature extracti...
215 篇 accuracy
183 篇 support vector m...
178 篇 predictive model...
138 篇 neural networks
138 篇 machine learning...
130 篇 computational mo...
121 篇 reinforcement le...
107 篇 convolutional ne...
103 篇 real-time system...
92 篇 forecasting
90 篇 artificial intel...
89 篇 learning systems
88 篇 transfer learnin...
87 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...
9 篇 school of inform...
8 篇 school of remote...
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

6,775 篇 英文
373 篇 其他
28 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 7159 条记录，以下是391-400 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：

An Automation Detection of Arrhythmia Using DWT-AR Features and Machine learning 11th

An Automation Detection of Arrhythmia Using DWT-AR Features ...

引用

11th international conference on intelligent Computing and Applications, ICRTC 2023

作者： Singh, Prem Narayan Mahapatra, Rajendra Prasad Department of Computer Science and Engineering Faculty of Engineering and Technology SRM Institute of Science and Technology Delhi-NCR Campus Delhi-Meerut Road Uttar Pradesh Ghaziabad Modinagar India

ISBN: (纸本)9789819717231

An irregular heartbeat is usually diagnosed using an electrocardiogram, the gold standard for making such a diagnosis (ECG). Researchers in machine learning have proved the volume and diversity of datasets utilized for method development to have a higher effect than the learning algorithm and techniques. In this paper, a new approach is designed using DWT-AR feature selection and classification by the three machine learning techniques. Testing on the MIT-BIH Arrhythmia database proves the robustness of the proposed algorithm. A hyper-tuning approach is a powerful tool for determining the hyperparameter in ML algorithms. Classifying ECG signals using SVM, ELM, and RVM reveals that RVM provides superior results across all parameters. the suggested program employs a morphological filter during preprocessing to prepare the data better for the DWT-AR modeling used in the ECG beat categorization. Compared to competing methods, it is shown to have superior precision, recall, detection rate, and false alarm to positive ratio (tnratio). © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Electrocardiograms

来源：评论

学校读者我要写书评

暂无评论

Research on vegetable automated operation decision-making based on data mining methods using random forest, LSTM-Seq2Seq, and NSGA-II 6

Research on vegetable automated operation decision-making ba...

引用

6th international conference on Information Science, Electrical, and Automation engineering, ISEAE 2024

作者： Zhou, Kai Liu, Zhaofeng Ai, Weixi Yang, Qiteng International College Chongqing University of Posts and Telecommunications Chongqing400065 China College of Science Hebei Agricultural University Hebei Baoding071001 China

ISBN: (纸本)9781510682924

Vegetables, characterized by short shelf life and easily perishable features, pose operational challenges for fresh food supermarkets in replenishing and pricing vegetable products within limited sales space. this study proposes an automated decision-making framework based on machine learning, data mining, and intelligent optimization algorithms, using a random forest model for regression prediction and an LSTM-based Seq2Seq model for time series prediction to address these challenges. the random forest model is trained using historical wholesale price data for regression prediction, with an average root mean square error (RMSE) of 0.7046 on the test set. In the time series prediction based on historical sales data, an LSTM-based Seq2Seq model is used, resulting in an average RMSE of 0.9631 on the test set. Subsequently, the random forest model is trained to predict actual sales volume based on the relationship between sales volume, wholesale price, and sales price, combining it with a multi-objective optimization model. the NSGA-II intelligent optimization algorithm is employed to solve the model. Ultimately, we determined various vegetables' sales prices and replenishment quantities by maximizing profits and minimizing supply surplus losses. the method proposed in this study helps improve supermarkets' operational efficiency and profits, providing new insights and methods for fresh food management decision-making. © 2024 SPIE.

关键词： Vegetables

来源：评论

学校读者我要写书评

暂无评论

8th international conference on intelligent Transport Systems, INTSYS 2024

8th International Conference on Intelligent Transport System...

引用

8th international conference on intelligent Transport Systems, INTSYS 2024

ISBN: (纸本)9783031863691

the proceedings contain 25 papers. the special focus in this conference is on intelligent Transport Systems. the topics include: Interoperable Traceability in Supply Chains: A Use Case in Agritech;treemob: Expressive Mobility data Representation through Tree-Based Structures;From GPS Traces to Individual Emission Exposure: A data-Driven Four-Step Process;capacity Vehicle Routing Problem with Time Windows: Simulation Tool for Footprint Network Design;chain of Portable Health Folders: A Systematic Literature Review;integrating Metro Infrastructure in Circular Food Supply Chains: A Model for Decentralized Quito’s Food Bank Network Redesign;An AutoML Approach for Bike Demand Forecasting and Redistribution;adaptive Stop-Skipping Scheduling Approach Using Reinforcement learning;machine learning Approach for Labeling Undetected Planned Trips in Public Transport Operators;reinforcement learning Algorithms with Graph Convolution Networks for Traffic Signal Control;optimizing intelligent Transportation Systems with Multi-agent Reinforcement learning: A Socio-economic Impact Assessment;a Mobile Application to Secure Pedestrians Interacting with automated Vehicles;A Simulation-Based Security Benchmarking Approach for Assessing Cooperative Driving Automation (CDA) Applications;wireless Interference and Regulatory Frameworks for Frequency Allocation in V2X Communication Systems;runtime Norms Regulation Framework for Drones’ Smart Cities Applications;a data-Driven Integrated Framework for Virtual Testing of Autonomous Vehicles in Mixed Traffic Scenarios;federated learning for Lane-Change Prediction;Evaluating Traffic Control Strategies for Autonomous Shuttle in Different AV Penetration, Using SUMO Traffic Simulation;Adaptive Video Bitrate Allocation for Remotely Operated Vehicles (ROV);experimental Evaluation of Road-Crossing Decisions by Autonomous Wheelchairs Against Environmental Factors;impact of Network Delays on Edge-Assisted Platooning Systems in 5G Networks: Addressing Lat

关键词：

来源：评论

学校读者我要写书评

暂无评论

Advanced Deep learning and Hybrid Models for Forecasting Rice Production in Indonesia 11

Advanced Deep Learning and Hybrid Models for Forecasting Ric...

引用

11th international conference on Information Technology, Computer and Electrical engineering, ICITACEE 2024

作者： Adiba, Jordan Istiqlal Qalbi Slamet, Joko Teguh, Andy Mohammad Septiyanto, Abdullah Faqih Sarno, Riyanarto Institut Teknologi Sepuluh Nopember Department of Informatics Surabaya Indonesia

ISBN: (纸本)9798350389289

Forecasting rice production supplies in Indonesia can help state planning by predicting rice production so that the state is able to determine decisions in various aspects such as inventory levels, procurement planning, distribution scheduling, resource allocation, and price strategies that will be taken based on forecasting results using artificial intelligence. this research focuses on developing proposed machine learning, deep learning, and hybrid models so that researchers can determine their respective abilities in executing data they collect from official Indonesian sites. the methods used in the research include the ARIMA model, LSTM, and the ARIMA-LSTM hybrid model. Several evaluation methods used in research are R2, MAE, RMSE, MAPE, and SMAPE. Based on research that has been conducted, the LSTM-ARIMA hybrid residual model outperforms every evaluation result with R2: 0.97, MAE: 0.15, RMSE: 0.18, MAPE: 7.26%, SMAPE: 7.06%. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Deep learning for Extracting Human Movement Patterns from Spatio-Temporal data 11

Deep Learning for Extracting Human Movement Patterns from Sp...

引用

11th IEEE international conference on intelligent Computing and Information Systems, ICICIS 2023

作者： Ezzat, Mahmoud Abdelkader, Tamer Badr, Nagwa Ain Shams University Faculty of Computer and Information Sciences Cairo Egypt

ISBN: (纸本)9798350322101

Human mobility data play an important role across various domains and applications by providing valuable insights into the movement of individuals, groups, and populations. Mining these data improves the ability to extract simple and complex human mobility patterns. these patterns are crucial for understanding the human behavior and predicting next-location of human movements that are essential for many applications, such as traffic forecasting, epidemic spreading, urban planning, and commuting flows. Great research efforts are spent to understand complex characteristics reflected in human mobility, and challenges related to trajectory data, such as time sensitivity, privacy risk assessment, sparsity, and higher-order dependencies. In this paper, we review recent approaches for extracting human movement patterns using deep learning techniques. We discuss these techniques and show their relevance to the different dimensions of human mobility data, challenges of trajectory data, and applications they can serve. through this study, we reveal the limitations of traditional machine learning models, and how deep learning models can overcome these limitations. Additionally, we discuss the important factors of privacy risk assessment that should be considered in human mobility. Finally, our review helps researchers to understand challenges of human mobility and demonstrate the future directions for leveraging deep learning to extract human movement patterns using the power of graph-based methods. © 2023 IEEE.

关键词： Risk assessment

来源：评论

学校读者我要写书评

暂无评论

Android-Based Augmented Reality as a learning Media for the Ancient Object History 11

Android-Based Augmented Reality as a Learning Media for the ...

引用

11th international conference on ICT for Smart Society, ICISS 2024

作者： Fitriani, Leni Tri Julianto, Indri Halimatul Hasanah, Eka Tresnawati, Dewi Institut Teknologi Garut Department of Informatics Engineering Garut Indonesia

ISBN: (纸本)9798350389654

this research aims to develop an Android-based augmented reality (AR) application to enhance the learning experience of ancient history. Traditional methods of teaching ancient objects often fail to engage students due to their static and two-dimensional nature. An AR application transforms these static images into interactive 3D models, providing a dynamic and immersive learning experience. the Research and Development (R&D) methodology, specifically the ADDIE model, involved stages of Analysis, Design, Development, Implementation, and Evaluation. the application was tested in a high school setting, significantly increasing student engagement and comprehension. the evaluation included alpha and beta testing phases involving teachers and students, resulting in an 88.58% satisfaction rate. the study concludes that AR technology has substantial potential to revolutionize educational practices by making learning more interactive and enjoyable. Future work will focus on expanding AR applications across different subjects and educational levels. © 2024 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Federated learning CNN for Broccoli Leaf Disease Control: A Path to Sustainable Farming 11

Federated Learning CNN for Broccoli Leaf Disease Control: A ...

引用

11th international conference on Reliability, Infocom Technologies and Optimization, ICRITO 2024

作者： Suryavanshi, Ankita Kukreja, Vinay Upadhyay, Deepak Mehta, Shiva thapliyal, Siddhant Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Graphic Era Hill University Computer Science and Engineering Uttarakhand Dehradun India Graphic Era Deemed to Be University Computer Science and Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350350357

A federated learning approach using convolutional neural networks (CNNs) for broccoli leaves' disease classification is described in our study. Here are a few highlights from the article. Using input from five varied clients, each representing a different cultivation scenario, we tackle the difficult task of classifying five separate classes of broccoli leaf diseases: healthy leaves, downy mildew, Alternaria leaf spot, black rot, and ring spot. On average, our federated learning CNN model reached an accuracy of 94.02%, recall of 94.54%, and F1-Score of 96.15%, proving its effectiveness. these results show that our federated learning model was able to provide an accurate classification of the five classes of broccoli leaf diseases. the model was able to identify standard features such as color, size, and shape to differentiate different courses. the weighted average, considering client performance and dataset sizes, equates to an F1-Score of 96.20%, a recall value of 94.53%, and precision at the said percentile was rounded up. In addition, considering all the clients and data sizes within dataset management, it does not miss out on accuracy, which stands at 94.03%, recall that is put up for standardization at 94.52%, and an F1-Score of 96%. these comprehensive results demonstrate that our federated learning model consistently and robustly classifies broccoli leaf diseases through diverse cultivation scenarios. this reinforces the ability of federated learning to overcome agricultural issues without compromising data confidentiality. © 2024 IEEE.

关键词： Cultivation

来源：评论

学校读者我要写书评

暂无评论

intelligent Emergency Notification Mobile Service via Multi-Task BERT Models 11

Intelligent Emergency Notification Mobile Service via Multi-...

引用

11th IEEE international conference on Mobile Cloud Computing, Services, and engineering, MobileCloud 2023

作者： Tan, Wenhao Zhang, Yanzhou Liu, Kaikai Computer Engineering Department San JoséCA United States

ISBN: (纸本)9798350322798

Mobile social networks have the potential to become the most effective platform for delivering urgent information during natural disaster events. Social media applications like Twitter are ideal for real-Time news delivery but lack many important features to become an effective emergency notification system. the most significant challenge is determining which news is an emergency and whether it is relevant to the user. In this project, we propose an intelligent emergency notification social network application that can automatically perform data mining from online social media platforms, filter out non-emergency and unrelated news, and deliver only classified emergency notifications to users. Rather than using multiple separate systems or machine learning models to achieve our goals, we propose a joint Multi-class Text Classification model based on BERT to filter out non-emergency tweets and classify the type of emergencies in one end-To-end neural network model. Additionally, we train a Named Entity Recognition (NER) model to extract locations from the classified emergency news. We evaluated our system in multiple historical emergency events and demonstrated the effectiveness of emergency news delivery using various performance metrics. © 2023 IEEE.

关键词： Neural network models

来源：评论

学校读者我要写书评

暂无评论

Synergizing Enhanced Neuro-Fuzzy System for Predictive Livestock Healthcare in Cloud IoT Environment 18

Synergizing Enhanced Neuro-Fuzzy System for Predictive Lives...

引用

18th INDIAcom;11th international conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Vigneswari, T. Sahapudeen, Farjana Farvin Geetha, S. Punitha Devi, C. Kalaiselvi, G. Anjalai Ammal Mahalingam Engineering College Department of Computer Science and Engineering Kovilvenni India Pondicherry University Department of Banking Technology Puducherry India

ISBN: (纸本)9789380544519

Livestock plays a crucial role in improving the economy of farmers but managing and monitoring livestock health pose significant challenges. With the advent of IoT and cloud computing, farmers now have the opportunity to intelligently monitor the health of their cattle. By leveraging machine learning techniques, the analysis of data collected from IoT devices enables the prediction of livestock health status. this paper presents an IoT-based cattle health monitoring system that tracks vital signs such as body temperature and heartbeat. the vital sign data is stored in the cloud and made available to the prediction system. To enhance the accuracy of health status predictions, this study introduces enhanced NeuroFuzzy Systems, which combine Multilayer Perceptron (MLP) and fuzzy inference systems. Experimental results demonstrate that the proposed system significantly improves the accuracy of health status prediction for livestock. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Cloud -IoT Fuzzy Inference System (FIS) Livestock monitoring Multilayer Perceptron(MLP)

来源：评论

学校读者我要写书评

暂无评论

Smart Education with DNA Testing: A Pathway to Personalized Academic Success 11

Smart Education with DNA Testing: A Pathway to Personalized ...

引用

11th international conference on ICT for Smart Society, ICISS 2024

作者： Hermanus, Davy Ronald Sasmoko Indrianti, Yasinta Research Interest Group in Educational Technology Bina Nusantara University Computer Science Department Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Research Interest Group in Educational Technology Bina Nusantara University Faculty of Humanities Primary Teacher Education Department Jakarta Indonesia Universitas Agung Podomoro Entrepreneurship Department Jakarta Indonesia

ISBN: (纸本)9798350389654

this paper examines the incorporation of DNA testing into intelligent education systems to develop customized learning plans that respond to the specific needs of each student. through the examination of distinct genetic indicators associated with personality traits, talent, and inborn abilities, educators can formulate approaches that optimize academic achievement and boost the overall welfare of students. this approach not only enhances learning outcomes but also promotes a supportive and inclusive educational environment. the study critically examines the present state of literature regarding the correlation between genetics and learning. It digs into the ethical implications surrounding this topic and shows case studies that provide evidence of the effectiveness of teaching methods informed by DNA analysis. the results underscore the capacity of DNA testing to transform education by enhancing its adaptability and responsiveness to the distinct genetic composition of individual students. this underscores the need for additional research and ethical guidelines to guarantee responsible integration in educational environments. © 2024 IEEE.

关键词： Federated learning

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 << < 36 37 38 39 40 41 42 43 44 45 > >>

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：