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

592 篇 会议
2 册 图书
1 篇 期刊文献

馆藏范围

595 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

365 篇 工学
- 337 篇 计算机科学与技术...
- 265 篇 软件工程
- 94 篇 生物工程
- 64 篇 信息与通信工程
- 64 篇 生物医学工程（可授...
- 24 篇 电气工程
- 15 篇 控制科学与工程
- 14 篇 光学工程
- 14 篇 化学工程与技术
- 10 篇 机械工程
- 10 篇 动力工程及工程热...
- 10 篇 土木工程
- 10 篇 农业工程
197 篇 理学
- 99 篇 生物学
- 96 篇 数学
- 43 篇 统计学（可授理学、...
- 37 篇 系统科学
- 33 篇 物理学
- 11 篇 化学
84 篇 管理学
- 50 篇 图书情报与档案管...
- 37 篇 管理科学与工程(可...
- 32 篇 工商管理
51 篇 医学
- 51 篇 基础医学(可授医学...
- 51 篇 临床医学
- 44 篇 药学(可授医学、理...
- 12 篇 公共卫生与预防医...
26 篇 法学
- 22 篇 社会学
15 篇 农学
- 15 篇 作物学
11 篇 经济学
- 11 篇 应用经济学
10 篇 教育学
- 10 篇 教育学
1 篇 军事学

主题

157 篇 machine learning
63 篇 machine learning...
59 篇 deep learning
36 篇 support vector m...
30 篇 computational mo...
25 篇 predictive model...
22 篇 prediction algor...
19 篇 informatics
17 篇 feature extracti...
17 篇 training
15 篇 decision trees
14 篇 forecasting
13 篇 internet of thin...
13 篇 cloud computing
13 篇 supervised learn...
12 篇 intrusion detect...
11 篇 medical services
11 篇 heart
11 篇 artificial intel...
11 篇 technological in...

机构

25 篇 department of co...
21 篇 uttaranchal inst...
18 篇 graphic era deem...
9 篇 uttaranchal inst...
7 篇 department of cs...
7 篇 department of co...
6 篇 chitkara univers...
6 篇 symbiosis instit...
5 篇 amity university...
5 篇 amity university...
5 篇 uttaranchal univ...
4 篇 maharashtra pune
4 篇 department of cs...
4 篇 department of co...
4 篇 vishwakarma univ...
4 篇 department of bi...
4 篇 faculty of engin...
4 篇 biomedical syste...
4 篇 department of el...
4 篇 engineering and ...

作者

9 篇 anita gehlot
7 篇 rajesh singh
7 篇 singh rajesh
7 篇 durgaprasad gang...
7 篇 gehlot anita
5 篇 sandeep kumar
5 篇 joel alanya-belt...
5 篇 alanya-beltran j...
5 篇 ramakrishnan ram...
5 篇 bhasker pant
4 篇 pundir sumit
4 篇 wan azani mustaf...
4 篇 hiam alquran
4 篇 vikas tripathi
4 篇 ahmed alkhayyat
4 篇 arora bhavna
4 篇 raman ramakrishn...
4 篇 devesh pratap si...
4 篇 kumar sandeep
4 篇 gangodkar durgap...

语言

590 篇 英文
5 篇 其他

检索条件"任意字段=5th Asia Conference on Machine Learning and Computing, ACMLC 2022"

共 595 条记录，以下是11-20 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：

Forecasting for Wind Farm Energy Output in South Australia: A Comparative Analysis of Physical Methods and Deep learning Methods 5

Forecasting for Wind Farm Energy Output in South Australia: ...

引用

5th asia conference on machine learning and computing, acmlc 2022

作者： Zhang, Yijia University of New South Wales School of Photovoltaic and Renewable Energy Engineering Sydney2033 Australia

ISBN: (纸本)9798350333923

To achieve the target of carbon zero' in 2050, the Australian government advocates the development of renewable energy technology to reduce CO2 emissions. Particularly, wind energy resources are rich in South Australia. With the development of wind farms, it is necessary to predict the energy output for the electricity market. this study compared two different methods for forecasting the wind energy output monthly. the first method is the physical method, using predicting weather data from Medium-Range Weather Forecasts (ECMWF). Another method is RNN-LSTM (Recurrent Neural Network-Long Short-Term Memory) by using Python to predict energy output. the result showed that the physical method can predict the trend of energy output value while RNN-LSTM is not suitable for monthly forecasting. this study proved that the deep learning methods should be utilized in the site that have numerous numbers of data resources. And it is better to use physical methods which consider the atmosphere, local terrain, and wind farm layout for wind farm energy outputs forecasting. © 2022 IEEE.

关键词： Wind power

来源：评论

学校读者我要写书评

暂无评论

A Method of Predicting Occupancy in Commercial Building Based on machine learning 5

A Method of Predicting Occupancy in Commercial Building Base...

引用

5th asia conference on machine learning and computing, acmlc 2022

作者： Zou, Qin Li, Nan Xu, Baowei Li, Xintong Chongqing University School of Civil Engineering Chongqing China Huawei Cloud Computing Technologies Co. Ltd. Cloud Data Center Mgmt Dept Dongguan China China Merchants Shekou Industrial Zone Holdings CO. Ltd. Chongqing China

ISBN: (纸本)9798350333923

As a reference value, the occupancy guides the building Automation System (BAS) operation, which can significantly reduce energy consumption. However, the occupancy counts of commercials fluctuate dynamically with time, and how to gain the occupancy clusters and accurately predict the occupancy counts has yet to be well solved. To solve the above problems, this research proposes a prediction method for the occupancy counts of commercial buildings based on the integration of Wi-Fi connection counts data, categories of weekdays and holidays, outdoor climate data sets, and the combination of K-Means and decision tree algorithm. First, the K-means algorithm was used to cluster to obtain the representative occupancy daily clusters. Subsequently, the decision tree algorithm recognizes the clusters' generation rules and constructs the prediction model. the validation experiments were conducted in a commercial building in Chongqing, China. the results showed that the prediction model had an accuracy of 95.24%, with better robustness than independent data sources. the prediction results can provide a practical reference for formulating BAS's operation control and commercial operation scheme in the low carbon emission reduction environment. © 2022 IEEE.

关键词： machine learning

来源：评论

学校读者我要写书评

暂无评论

Mobile-Based Navigation Assistant for Visually Impaired Person with Real-time Obstacle Detection Using YOLO-based Deep learning Algorithm 5

Mobile-Based Navigation Assistant for Visually Impaired Pers...

引用

5th asia conference on machine learning and computing, acmlc 2022

作者： Catedrilla, Gene Marck B. Laguna State Polytechnic University College of Computer Studies Laguna Philippines

ISBN: (纸本)9798350333923

this project mainly aims to develop a mobile-based application for navigation with real-time obstacle detection to provide fair access to people with visual impairment to some activities, specifically navigating outdoors. It is a navigation mobile application equipped with speech and gesture recognition, to allow the people with visual impairment to access and use the application, and obstacle detection to provide audio prompts to the user, so they will know whenever an object or obstacle is within the frame of the phone camera. the research was structured and accomplished through different scientific and technological process and approach. With the use of Dialog flow, it was possible to create a speech recognition feature for the application, while YOLO algorithm allowed the process of object detection using mobile phone camera, possible. In this research, it was found out that the application was applicable to improving the navigation of the visually impaired, it is ideal that it serves as supplement to the white stick in order to improve their navigation experience. Also, this project would like to emphasize that researches that seeks to help person with disability be considered and conducted by other researchers. © 2022 IEEE.

关键词： Navigation

来源：评论

学校读者我要写书评

暂无评论

Deep learning for Detecting Malaria Parasites of Infected Red Blood Cells in thin Blood Smear Images 5

Deep Learning for Detecting Malaria Parasites of Infected Re...

引用

5th asia conference on machine learning and computing, acmlc 2022

作者： Naksuwan, Wongsathon Suwannahitatorn, Picha Watcharopas, Chakrit Wattuya, Pakaket Kasetsart University Department of Computer Science Bangkok Thailand Kasetsart University Artificial Intelligence Technology and Innovation Center for Health Faculty of Science Bangkok Thailand Phramongkutklao College of Medicine Department of Parasitology Bangkok Thailand

ISBN: (纸本)9798350333923

Malaria is a significant global health issue, with 241 million people infected and resulting in 627,000 deaths in 2020, officially reported by the World Health organization (WHO). In addition, during the Covid-19 pandemic, 47,000 people died because of a reluctance to receive treatment. In thailand, Malaria still spreads in distant communities where restrictions are in place for military deployments due to the high risk of infection. therefore, the 8,000 or so military personnel who deploy on missions close to the country's borders are actively monitored by the Armed Forces Research Institute of Medical Sciences (AFRIMS). the lack of medical personnel in these remote settlements, however, slows detection and adversely impacts the health and lives of military soldiers working in these locations. Because of their comparative effectiveness to traditional learning algorithms, deep learning technologies are used as a tool for medical screenings. In this study, the YOLOv3 and the DenseNetl21 are used to diagnose malaria infection using thin film blood smears. the results show that testing on normal slide datasets can distinguish between normal red blood cells and malaria-infected red blood cells in four species, including Falciparum, Vivax, Malariae, and Ovale, with accuracy for infection classification at 98.08%, sensitivity at 98.05%, and specificity at 99.73%. Furthermore, when the hard slide dataset is examined, the infection classification's accuracy, sensitivity, and specificity are 98.48%, 90%, and 99.24%, respectively. In normal slide datasets, this detection method yields a positive hit rate for malaria-infected red blood cells and normal red blood cells of 98.05% for the former and 92.65% for the latter. © 2022 IEEE.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Application of machine learning in Enterprise Financial Risk Assessment: A Study About China's A-Share Listed Manufacturing Companies 5th

Application of Machine Learning in Enterprise Financial Risk...

引用

5th International conference on Neural computing for Advanced Applications (NCAA)

作者： Yul, Kexin Yul, Zengyi Ma, Shuomin Xu, Pan Zhejiang Univ Technol Hangzhou 310023 Peoples R China SpringAI LLC Bellevue WA 98007 USA

ISBN: (纸本)9789819770038;9789819770045

Based on the financial data of domestic A-share listed firms from 2000 to 2022, this paper aims to explore the effectiveness of machine learning in identifying the financial risk of Chinese A-share listed manufacturing firms. To this end, a variety of machine learning models, including logistic regression, decision tree, random forest, XGBoost, SVM, and LSTM, are used to assess the financial risk of enterprises, and the key attributes of enterprise financial risk are extracted through the interpretability exploration and importance coefficient measurement. From this paper, the following conclusions are drawn: (i) XGBoost model performs the best on all attributes, showing its strong ability in dealing with complex financial datasets, and LSTM, which adds time-series factors, performs poorly, which is speculated that it may be related to the incompatibility of the characteristics of the financial data, the reliance on the time-series features, and the need for financial fine features. (ii) Audit opinion, Net Profit and ROA are key influencing factors.

关键词： Financial risk machine learning XGBoost LSTM

来源：评论

学校读者我要写书评

暂无评论

Semi-asynchronous federation optimization method based on buffer pre-aggregation 24

Semi-asynchronous federation optimization method based on bu...

引用

5th International conference on computing, Networks and Internet of things (CNIOT)

作者： Chen, Yimi Zheng, Xianghan Zhan, Yichen Fuzhou Univ Fuzhou Peoples R China Univ Sanya Sanya Peoples R China Fujian Petrochem Ind Design Inst Co Ltd Fuzhou Peoples R China

ISBN: (纸本)9798400716751

As a distributed machine learning framework, federated learning has received considerable attention in recent years and has been researched and applied in various scenarios. However, the system heterogeneity due to the physical characteristics of various terminal devices has led to the straggler effect, making the practical implementation of federated learning challenging. therefore, we propose a semi-asynchronous federated optimization method based on buffer pre-aggregation. this method allows every participant to engage in training through pre-aggregation and establishes a training time framework based on the pre-aggregation time. It updates the model adaptively using a semi-asynchronous communication method combined with lag factors, improving communication efficiency while maintaining stable accuracy. Experimental results on datasets demonstrate that our proposed method can effectively accelerate the training process of federated learning compared to existing federated optimization methods.

关键词： Federated learning Semi-Asynchronous Communication Distributed machine learning

来源：评论

学校读者我要写书评

暂无评论

conference Organization

Conference Organization

引用

machine learning and computing (acmlc), asia conference on

来源：评论

学校读者我要写书评

暂无评论

Data Mining in Mobile learning: Uncovering Insights for Enhanced Vocabulary Acquisition 6

Data Mining in Mobile Learning: Uncovering Insights for Enha...

引用

6th Artificial Intelligence and Cloud computing conference (AICCC) / 5th asia Digital Image Processing conference

作者： Wu, Minghai Shenyang Jianzhu Univ Sch Foreign Languages Shenyang Peoples R China

ISBN: (纸本)9798400716225

the integration of mobile learning and machine learning, driven by the proliferation of smart handheld devices and the vast amount of learning resources available on the internet, has revolutionized education. this study explores the use of mobile learning, specifically leveraging mobility and big data mining techniques, to improve college English vocabulary acquisition among university students. By addressing the challenges faced in mobile learning and applying innovative methodologies, we have developed a personalized recommendation system based on data mining algorithms. this system suggests English vocabulary words to students based on their past performance, harnessing the power of big data mining. through a comprehensive evaluation, we have demonstrated the effectiveness of our approach in enhancing vocabulary acquisition and retention compared to traditional book-based learning methods. the findings of this research not only contribute to the advancement of mobile learning but also provide valuable insights for educators and policymakers on the effective utilization of mobility and big data mining for enhanced student learning outcomes.

关键词： Data mining Mobile learning College English vocabulary acquisition machine learning

来源：评论

学校读者我要写书评

暂无评论

A Survey on Deep learning-Based Medical Image Registration 5th

A Survey on Deep Learning-Based Medical Image Registration

引用

5th International conference on Neural computing for Advanced Applications (NCAA)

作者： Xu, Ronghao Liu, Chongxin Liu, Shuaitong Huang, Weijie Zhang, Menghua Univ Jinan Sch Elect Engn Jinan 250000 Peoples R China

ISBN: (纸本)9789819770007;9789819770014

In recent years, various methods have been proposed to address the fundamental task of medical image registration in medical image analysis. this paper systematically reviews the research progress in medical image registration using deep learning techniques. these methods utilize deep learning algorithms to achieve precise alignment of medical image data from different modalities, time points, or sources, thereby providing dependable help for clinical identification and care. this paper seeks to provide researchers and practitioners with the most current technological advances and potential applications in the realm of medical image registration.

关键词： Image registration Deep learning CNN Supervised learning

来源：评论

学校读者我要写书评

暂无评论

Application of PRA and machine learning Algorithm in Budget Data Acquisition and Processing System

Application of PRA and Machine Learning Algorithm in Budget ...

引用

machine learning and computing (acmlc), asia conference on

作者： Chenhong Zheng Mengqian Zhang Ying Wang Meihua Zou State Grid Fujian Economic Research Institute Fuzhou China

How to use automation, optimize the comprehensive budget management system, and help the automatic collection of budget data and budget preparation has become a growing concern for enterprises. this paper combines IT technologies such as robot process automation (PRA) and machine learning algorithm with comprehensive budget management, optimizes the budget data collection process, conducts budget data mining and analysis, so as to help enterprises formulate budget plans, and puts forward implementation suggestions and safeguards.

关键词：

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60页 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：