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

297 篇 期刊文献
241 篇 会议
5 篇 学位论文

馆藏范围

543 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

447 篇 工学
- 267 篇 计算机科学与技术...
- 137 篇 电气工程
- 84 篇 信息与通信工程
- 57 篇 控制科学与工程
- 47 篇 软件工程
- 31 篇 仪器科学与技术
- 22 篇 机械工程
- 21 篇 生物医学工程（可授...
- 19 篇 测绘科学与技术
- 19 篇 环境科学与工程（可...
- 15 篇 化学工程与技术
- 13 篇 电子科学与技术（可...
- 13 篇 网络空间安全
- 11 篇 材料科学与工程（可...
- 9 篇 石油与天然气工程
- 9 篇 交通运输工程
- 7 篇 生物工程
- 6 篇 动力工程及工程热...
123 篇 理学
- 36 篇 数学
- 36 篇 生物学
- 23 篇 物理学
- 23 篇 化学
- 13 篇 地球物理学
- 7 篇 统计学（可授理学、...
84 篇 管理学
- 73 篇 管理科学与工程(可...
- 8 篇 公共管理
52 篇 医学
- 28 篇 临床医学
- 24 篇 基础医学(可授医学...
23 篇 农学
- 10 篇 作物学
7 篇 经济学
- 6 篇 应用经济学
6 篇 教育学
5 篇 法学
2 篇 文学
1 篇 艺术学

主题

543 篇 classification a...
98 篇 machine learning
38 篇 feature extracti...
37 篇 data mining
28 篇 feature selectio...
19 篇 support vector m...
14 篇 deep learning
12 篇 random forest
12 篇 support vector m...
11 篇 classification a...
10 篇 clustering algor...
10 篇 decision tree
9 篇 fault diagnosis
8 篇 ensemble learnin...
8 篇 svm
8 篇 big data
8 篇 artificial intel...
7 篇 learning (artifi...
7 篇 accuracy
7 篇 machine learning...

机构

4 篇 city univ hong k...
3 篇 univ elect sci &...
3 篇 yonsei univ yons...
3 篇 yonsei univ dept...
3 篇 jiangsu univ dep...
2 篇 queens univ dept...
2 篇 hangzhou dianzi ...
2 篇 korea univ sch i...
2 篇 virginia polytec...
2 篇 jiangsu univ sch...
2 篇 shanghai maritim...
2 篇 yunnan univ sch ...
2 篇 tianjin univ col...
2 篇 hubei univ techn...
2 篇 iiit delhi dept ...
2 篇 university of ch...
2 篇 brno university ...
2 篇 arizona state un...
2 篇 intercell ag a-1...
2 篇 kiit deemed univ...

作者

4 篇 zhou ding-xuan
3 篇 xia ji'an
3 篇 roy asim
3 篇 chen quansheng
3 篇 zhang yan
3 篇 zhao jiewen
3 篇 sharma anuradha
3 篇 peng yi
3 篇 sun yunshan
3 篇 han sanghoon
3 篇 zhang liyi
3 篇 qin yong
3 篇 shen yan
3 篇 yadav monika
2 篇 ding wei
2 篇 cobourn kelly m.
2 篇 priambodo bagus
2 篇 wang jing
2 篇 zhang wenyu
2 篇 shatabda swakkha...

语言

518 篇 英文
20 篇 其他
3 篇 中文
2 篇 土耳其文
1 篇 德文
1 篇 法文

检索条件"主题词=Classification Algorithm"

共 543 条记录，以下是431-440 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：

A novel gender classification method based on MapReduce

A novel gender classification method based on MapReduce

引用

IEEE International Conference on Software Engineering and Service Sciences (ICSESS)

作者： Tong Cui Haifeng Zhao Science and Technology on Information Systems Engineering Laboratory Nanjing China

ISBN: (纸本)9781479983544

A novel parallelize gender recognition method with MapReduce is presented, which successfully comprise several machine leaning algorithms which are employed for gender recognition. The mass of face sample images are gathered and separated as train dataset and test dataset, and Local Binary Pattern (LBP) features are extracted when those sample sets are pre-processed and made ready for following operations. And Principle Component Analysis (PCA) is applied to train dataset to extract the most distinguishing features. Three classification algorithms: Support Vector Machine(SVM), k-Nearest Neighborhood (k-NN) and Adaboost are implemented and compared to determine the most suitable and successful algorithm for gender parallelize machine learning (GPML). To achieve the shortest execution time, we propose to apply GPML with MapReduce to avoid parallelizing above three algorithms while also improving their scalability to big datasets. The results show that this method reduces the training computational complexity significantly when the number of computing nodes increases while gaining better speedup rates and extending performance than those on parallelize Adaboost.

关键词： face recognition feature extraction image classification learning (artificial intelligence) parallel processing principal component analysis support vector machines Adaboost GPML LBP features MapReduce PCA SVM classification algorithm face sample images gender classification method gender parallelize machine learning k-nearest neighborhood local binary pattern feature extraction machine leaning algorithms parallelized gender recognition method principle component analysis support vector machine test dataset train dataset training computational complexity gender recognition parallel meta-learning Support Vector Network principal components analysis Sorting algorithm Image classification PARALLEL PROCESSING (COMPUTERS) Facial Recognition Passive Cutaneous Anaphylaxis Feature extraction Dataset Gender ADABOOST execution time classification Methods

来源：评论

学校读者我要写书评

暂无评论

Study on Vegetation classification Based on Spectral Knowledge Base

Study on Vegetation Classification Based on Spectral Knowled...

引用

The International Conference on Intelligent Agriculture 2017(ICIA2017)

作者： Peng Liu Jingcheng Zhang Bin Wang Xuexue Zhang Kaihua Wu College of Life Information Science and Instrument Engineering Hangzhou Dianzi University

ISBN: (纸本)9783030061784

A framework about spectral based vegetation classification was proposed, which serves as a core methodology of the vegetation spectral knowledge base. The hyperspectral reflectances of 13 types of plants were measured by an ASD FieldSpec 4 spectroradiometer. Two forms of spectral features were used for representing the key spectral characteristics of plants,including Vegetation index(VI) and spectral shape features. Based on these spectral features, a sensitivity analysis was performed to identify the most important features for establishing the classifier. The analysis of variance(ANOVA) and the cross-correlation analysis were applied to derive the sensitivity of features and remove features that have high correlations. Then, a classification method for differentiating plants was established by coupling some spectral similarity measures(e.g., ED) with some classification methods(e.g.,BPANN and SVM). The results of discrimination analysis showed that a highest accuracy was produced by SVM with the OAA over 99% when using 7 sensitive VIs. The results suggested the framework about spectral based vegetation classification can form a basis for spectral knowledge base and application technology and further achieve a wide range of plant classification based on remote sensing.

关键词： Vegetation classification Hyperspectral Feature extraction classification algorithm

来源：评论

学校读者我要写书评

暂无评论

Research on Characteristics Analysis and classification of Microblog Users

Research on Characteristics Analysis and Classification of M...

引用

2015 3rd International Conference on Machinery,Materials and Information Technology Applications(ICMMITA 2015)

作者： Jiang Xin Li WenMin State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications

Microblog has become an important part of social media, a large number of users send and thus spread information on this platform. Nowadays, the network environment of microblog is impacted by the presence of anomalies in users seriously. So the research on identifying the types of microblog users is of great significance. Based on the example of microblog, this paper selects some microblog users as research objects and thus analyzes and extracts the features of the selected users. Meanwhile, it uses statistical methods and classification methods in data mining to analyze user data. With the breakthrough point, the classification method C4.5 Decision Tree, this paper has trained the history data to form a classifier to make prognostic classification of new sample, which has realized high accuracy.

关键词： Microblog Users Feature Detection classification algorithm C4.5 Decision Tree

来源：评论

学校读者我要写书评

暂无评论

Change detection for activity recognition.

Change detection for activity recognition.

引用

作者： BASHIR, S. A. Robert Gordon University

学位级别：博士

Activity Recognition is concerned with identifying the physical state of a user at a par- ticular point in time. Activity recognition task requires the training of classification algorithm using the processed sensor data from the representative population of users. The accuracy of the generated model often reduces during classification of new instances due to the non-stationary sensor data and variations in user characteristics. Thus, there is a need to adapt the classification model to new user characteristics. However, the existing approaches to model adaptation in activity recognition are blind. They con- tinuously adapt a classification model at a regular interval without specific and precise detection of the indicator of the degrading performance of the model. This approach can lead to wastage of system resources dedicated to continuous adaptation. This thesis addresses the problem of detecting changes in the accuracy of activity recog- nition model. The thesis developed a classifier for activity recognition. The classifier uses three statistical summaries data that can be generated from any dataset for sim- ilarity based classification of new samples. The weighted ensemble combination of the classification decision from each statistical summary data results in a better performance than three existing benchmarked classification algorithms. The thesis also presents change detection approaches that can detect the changes in the accuracy of the underlying recognition model without having access to the ground truth label of each activity being recognised. The first approach called 'UDetect' computes the change statistics from the window of classified data and employed statistical process control method to detect variations between the classified data and the reference data of a class. Evaluation of the approach indicates a consistent detection that correlates with the error rate of the model. The second approach is a distance based change detection technique that r

关键词： Activity Recognition Change Detection classification algorithm Sensors

来源：评论

学校读者我要写书评

暂无评论

FEATURE SELECTION IN MEDICAL DOMAINS

FEATURE SELECTION IN MEDICAL DOMAINS

引用

作者： SARA VAHID University of Georgia

学位级别：硕士

Usually datasets in the medical domain contain so many features while not all these features are useful for training the classifier. This research aims to find the best optimal subset of features for each medical datasets namely Heart Disease, Parkinson, Thoracic Surgery, Diabetic Retinopathy and Breast Cancer which are all publicly available in UCI repository. We use Filter and Wrapper as feature selection methods which are scheme independent and scheme specific, respectively. In Wrapper approach, we applied different classification algorithms such as Support Vector Machine (SVM), Naive Bayes, Decision Tree, Random Forest and K Nearest Neighbor (KNN) for both feature selection and classification. Afterwards, the same classifiers were applied on the dataset with selected features. The target of this study is comparative analysis of the effect of feature selection on 5 aforementioned datasets (these datasets are various in terms of data types and dimensionality) regarding the accuracy of the classifier.

关键词： Feature Selection Machine Learning classification algorithm Medical Domain

来源：评论

学校读者我要写书评

暂无评论

Towards the Development of a Smart Parking System for Highly Populated Cities

Towards the Development of a Smart Parking System for Highly...

引用

2023 International Conference on Science, Engineering and Business for Sustainable Development Goals, SEB-SDG 2023

作者： Ogundokun, Roseline Oluwaseun Soladoye, Elijah Iseoluwa Asani, Emmanuel Oluwatobi Akande, Oladipupo Ishola, Oluwaseun Joshua Akinwumi, Oyinkansola Aremu, Charity Onye Babatunde, Akinbowale Nathaniel Landmark University Department of Computer Science Omu Aran Nigeria Kaunas University of Technology Department of Multimedia Engineering Lithuania Kwara State University Department of Computer Science Malete Nigeria

ISBN: (纸本)9798350324785

Thanks to innovative sensing systems for smart cities that integrate the future into the present, civilization is through one of its brief transitional phases. The congestion of urban areas necessitates the creation of an adaptable strategy formulation that integrates architecture, creativity, and technology to accommodate paradigm change. A unique sensor approach that is the foundation of a smart parking system (SPS) is provided to enhance accessibility in municipalities with an increasing vehicle pool. The SPS consists of a small single-board computer, a proximity sensor, a camera, a LED indication, a buzzer, and a battery and is designed to determine the availability of a parking spot. This smart transportation technology comprises three major components, specifically sensors, a mobile application, and a monitoring centre, all of which collaborate to monitor, regulate, analyze, and show real-time parking spot information to drivers. Also, the design and execution of the three components of the overall system are shown. © 2023 IEEE.

关键词： Churn prediction classification algorithm Dimensionality reduction Oversampling technique

来源：评论

学校读者我要写书评

暂无评论

Comparative Studies on Activity Recognition of Elderly People Living Alone

Comparative Studies on Activity Recognition of Elderly Peopl...

引用

2019 Chinese Intelligent Systems Conference

作者： Xu, Zimin Wang, Guoli Guo, Xuemei Sun Yat Sen Univ Sch Data & Comp Sci Guangzhou 510006 Peoples R China Minist Educ Key Lab Machine Intelligence & Adv Comp Guangzhou Peoples R China

ISBN: (纸本)9789813296848;9789813296824;9789813296817

The social phenomenon of empty nesters is becoming more and more ubiquitous, and it is difficult to keep a watchful eye on their conditions. The advancement of computer technology and the spread of related applications have promoted the study of pervasive computing and smart cities. Ambient assisted living (AAL) systems have also been born in response to trends and demands. Regarding to medical surveillance, the AAL systems can care for the elderly people living alone full time, provide health advice, and initiate an early warning model when an emergency is detected. Main intention of this paper is to make comparative studies on activity recognition of elderly people living alone utilizing 6 classic classification algorithms, namely decision tree (DT), k-nearest neighbor (KNN), support vector machine (SVM), naive Bayes (NB), linear discriminant analysis (LDA), and ensemble learning (EL). And we adopt these models to recognize 10 activities of daily living (ADLs), namely Meal_Preparation, Relax, Eating, Work, Sleeping, Wash_Dishes, Bed_to_Toilet, Enter_Home, Leave_Home and Housekeeping. In this work, we employ the Aruba annotated open dataset that obtained in a smart house where a voluntary single elderly woman has lived for 220 days. After structuring and cleaning data, we slice data according to entire activity and then extract features from these activity units. Results show that most classification algorithms perform well except for NB based on the activity features we extract. In the future, we can boost performance through improving algorithms, automatically extracting features, and changing the way of reproducing activity representation.

关键词： Activity recognition classification algorithm Wireless sensor network Data preprocessing Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Investigating the Impacts of Weather and Personalisation on Asthma Exacerbations using Machine Learning 2022

Investigating the Impacts of Weather and Personalisation on ...

引用

11th International Conference on Software and Computer Applications, ICSCA 2022

作者： Haque, Radiah Ho, Sin-Ban Chai, Ian Abdullah, Adina Faculty of Computing and Informatics Multimedia University Malaysia Faculty of Medicine University of Malaya Malaysia

ISBN: (纸本)9781450385770

This paper reports the results of investigating the impacts of weather and personalisation on asthma exacerbations. Additionally, several machine learning classification algorithms were applied and evaluated to develop an intelligent mHealth solution that can offer accurate personalised estimations of asthma exacerbations based on weather and demography and provide tailored precautionary guidelines for selfcare to each user. Consequently, the proposed solution will enhance asthma self-management by assisting patients with chronic asthma to plan their daily outdoor activities and limit exposure to weather triggers, thus controlling their asthma exacerbations. © 2022 ACM.

关键词： Machine learning Neural networks Personalisation Asthma self-management classification algorithm

来源：评论

学校读者我要写书评

暂无评论

Liver Tumour Parameter Prediction Using Feature Extraction and Supervised Function 1

Liver Tumour Parameter Prediction Using Feature Extraction a...

引用

1st International Conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023

作者： Kumar, Ankit Singh, Kamred Udham Singh, Teekam Banu, Nargis Rathore, Yogesh Kumar Pandey, Saroj Kumar Gla University Department of Computer Engineering & Apllications UP Mathura India School of Computing Graphic Era Hill University Dehradun India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India Geetanjali Institute of Technical Studies Dabok Udaipur India India

ISBN: (纸本)9798350330915

The process of extracting features is essential to simplifying and condensing a wide variety of data dimensions while at the same time combining essential factors into a single influential parameter. In the field of medical research, predicting liver tumours represents a daunting task, which calls for the development of a more advanced detection mechanism that is focused towards achieving higher levels of identification precision. Even though experienced medical professionals can make preliminary predictions regarding liver tumours based on their clinical experience and diagnostic tools such as imaging and scans, there is still a compelling need for systematic assistance in making a final decision. This is especially true when evaluating patient symptoms. For the sake of our application, the approach of feature extraction that we have choose to use is called linear discriminant analysis (LDA). LDA displays its usefulness by being able to accommodate classification techniques with more than two classes and by exceeding logistic regression in terms of accuracy of classification. We make use of the power of supervised functions, in particular decision trees and the Naive Bayes algorithm, in order to make an accurate prediction about the existence of liver illness. These algorithms produce predictions regarding the existence of liver disease with a high degree of accuracy by using the factors discovered during LDA analysis. For the purposes of our simulation work, we make use of the flexible scikit-learn library in Python. This library offers a dependable infrastructure for the performance of machine learning activities. The part of this research under 'Methodology and Implementation' digs into the specifics of our approach and outlines the actions that are required to evaluate the effectiveness of our prediction model. © 2023 IEEE.

关键词： classification algorithm feature extraction LDA Linear Discriminant Analysis Liver tumor Supervised function Supervised function

来源：评论

学校读者我要写书评

暂无评论

Research on Machine Learning Method for Extracting Malicious Web Page Features 11

Research on Machine Learning Method for Extracting Malicious...

引用

11th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2023

作者： Wang, Lin School of Marxism Hohai University Nanjing China

ISBN: (纸本)9798350333664

Based on the analysis of traditional webpage features of several malicious web pages: webpage URL, JavaScript code, and HTML code, this article defines several features for malicious web page recognition;Proposed several features based on HTTP request information;And a malicious web page recognition method based on feature fusion and machine learning was proposed, which combines HTTP request features with traditional web page features, and then uses machine learning classification algorithms to construct a web page classification model to distinguish between normal and malicious web pages. Select 500 normal web pages from Alexa, and select a total of 500 web pages from PhishTank and Malwaredomains as malicious web pages to construct a dataset and train a web page classification model. Through experiments, it was verified that the method based on URL features, webpage code features, and HTTP request features is superior to the method without HTTP request features, and it was found that the random forest classification algorithm is more suitable for malicious webpage recognition. © 2023 IEEE.

关键词： classification algorithm Feature selection Machine learning Malicious web pages

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55页 << < 40 41 42 43 44 45 46 47 48 49 > >>

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：