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

22,737 篇 会议
3,246 篇 期刊文献
19 篇 学位论文
7 册 图书

馆藏范围

26,008 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

5,167 篇 工学
- 3,101 篇 计算机科学与技术...
- 2,550 篇 电气工程
- 1,389 篇 信息与通信工程
- 689 篇 控制科学与工程
- 593 篇 软件工程
- 286 篇 仪器科学与技术
- 219 篇 环境科学与工程（可...
- 189 篇 机械工程
- 184 篇 生物医学工程（可授...
- 163 篇 交通运输工程
- 150 篇 测绘科学与技术
- 130 篇 生物工程
- 123 篇 石油与天然气工程
- 121 篇 电子科学与技术（可...
- 118 篇 材料科学与工程（可...
- 111 篇 网络空间安全
- 96 篇 土木工程
- 92 篇 动力工程及工程热...
- 65 篇 水利工程
944 篇 理学
- 289 篇 生物学
- 188 篇 物理学
- 157 篇 化学
- 139 篇 地球物理学
- 133 篇 数学
- 84 篇 系统科学
612 篇 管理学
- 525 篇 管理科学与工程(可...
- 69 篇 图书情报与档案管...
439 篇 医学
- 284 篇 临床医学
- 96 篇 基础医学(可授医学...
227 篇 农学
- 148 篇 作物学
53 篇 经济学
51 篇 法学
49 篇 文学
48 篇 教育学
17 篇 艺术学
3 篇 军事学
2 篇 哲学

主题

26,009 篇 machine learning...
8,393 篇 machine learning
4,275 篇 support vector m...
4,229 篇 accuracy
4,193 篇 prediction algor...
3,613 篇 predictive model...
3,490 篇 training
3,223 篇 classification a...
3,187 篇 feature extracti...
1,954 篇 data models
1,815 篇 computational mo...
1,787 篇 deep learning
1,683 篇 random forests
1,468 篇 neural networks
1,400 篇 real-time system...
1,398 篇 clustering algor...
1,276 篇 data mining
1,149 篇 optimization
1,004 篇 decision trees
977 篇 measurement

机构

120 篇 chitkara univers...
39 篇 lovely professio...
36 篇 chitkara centre ...
30 篇 computer science...
30 篇 centre of resear...
28 篇 department of co...
26 篇 school of comput...
21 篇 univ chinese aca...
21 篇 computer science...
21 篇 school of comput...
20 篇 computer science...
18 篇 school of comput...
17 篇 school of comput...
17 篇 department of co...
16 篇 brac university ...
16 篇 khulna universit...
15 篇 symbiosis instit...
14 篇 department of co...
13 篇 school of comput...
13 篇 computer science...

作者

25 篇 ashwini kodipall...
24 篇 mahendra kumar g...
15 篇 rakesh kumar
13 篇 wei liu
13 篇 atul kumar
12 篇 qiangfu zhao
12 篇 amit kumar
12 篇 surendran r
12 篇 satvik vats
11 篇 jun zhang
11 篇 li li
11 篇 liu yang
11 篇 wei li
10 篇 sudeep tanwar
10 篇 himanshu sharma
10 篇 amiya ranjan pan...
9 篇 lei wang
9 篇 tohari ahmad
9 篇 shanmugasundaram...
9 篇 rishabh sharma

语言

25,798 篇 英文
153 篇 其他
33 篇 中文
4 篇 法文
2 篇 西班牙文
2 篇 荷兰文
2 篇 土耳其文

检索条件"主题词=Machine Learning Algorithms"

共 26009 条记录，以下是1761-1770 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：

Performance Analysis on Student Feedback using machine learning algorithms

Performance Analysis on Student Feedback using Machine Learn...

引用

International Conference on Advanced Computing and Communication Systems (ICACCS)

作者： Sharnitha Katragadda Varshitha Ravi Prasanna Kumar G. Jaya Lakshmi VR Siddhartha Engineering College Vijayawada India

ISBN: (数字)9781728151977

ISBN: (纸本)9781728151984

It investigates opinion mining by means of supervised learning techniques to search out the emotion of the student input bolstered characterized choices of instructing and learning. The examination led includes the apparatus of a blend of AI and common language preparing systems on understudy input data accumulated from module investigation overview consequences of VR Siddhartha Engineering College, Vijayawada. Additionally, to offer a grade by grade clarification of the technique of accomplishment of opinion mining on or after scholar remarks using the open source tool Python, the work additionally offers a comparative overall performance take a look remarks supported, extracted alternatives like examination, teaching and so on. The consequences are as compared to be trying to find out higher overall performance with relevance several evaluation standards designed for the various techniques.

关键词： Data mining machine learning algorithms Support vector machines Artificial neural networks Classification algorithms Sentiment analysis Supervised learning

来源：评论

学校读者我要写书评

暂无评论

Predicting employee turnover intention in IT&ITeS industry using machine learning algorithms

Predicting employee turnover intention in IT&ITeS industry u...

引用

International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： S K Monisaa Tharani S N Vivek Raj KCT Business School Kumaraguru College of Technology Coimbatore India

ISBN: (数字)9781728154640

ISBN: (纸本)9781728154657

Employee' determination to leave the organization is one of the significant factors impacting the performance of the organizations since it affects the overall profitability. Organizations need to strategize to reduce the turnover goals of the workers to have a competitive advantage over other organizations. By understanding the factors impacting the employee's intent to leave the organization, the management can intervene with strategic policies and decisions so that intent of the employees to leave the organization will be reduced substantially and thus increasing the employee's engagement towards work. This research paper uses machine learning algorithms to predict an employee's intention to leave the organization in the near future and identifies the significant features impacting the employee's intention to leave the organization. Data has been collected from 416 employees working in IT and ITES companies using convenience sampling and structure questionnaire. Research also used text mining to analyse the open-ended questionnaire filled by the employees there by mining the frequently used words and employee sentiments. From the study, it is found that among the Classification algorithms used for predicting employee's turnover intention, XG boost performed relatively better with high accuracy, recall, precision and f score. Using Logistic Regression, it is found that alternative job opportunity, gender, education, willing to relocate from the workplace, alternative job opportunity, job stress and attitude towards COVID affects the employee's intent to leave the organization to a greater extent.

关键词： Text mining Industries machine learning algorithms Profitability Organizations Stress Logistics

来源：评论

学校读者我要写书评

暂无评论

Detecting a Stealthy Attack in Distributed Control for Microgrids using machine learning algorithms

Detecting a Stealthy Attack in Distributed Control for Micro...

引用

Industrial Cyber-Physical Systems (ICPS)

作者： Mingxiao Ma Abdelkader Lahmadi Isabelle Chrisment CNRS Inria Loria Universite de Lorraine Nancy France

ISBN: (数字)9781728163895

ISBN: (纸本)9781728163901

With the increasing penetration of inverter-based distributed generators (DG) into low-voltage distribution microgrid systems, it is of great importance to guarantee their safe and reliable operations. These systems leverage communication networks to implement a distributed and cooperative control structure. However, the detection of stealthy attacks with a large impact and weak detection signals on such distributed control systems is rarely studied. In this paper, we address the problem of detecting a stealthy attack, named MaR, on the communication network of a microgrid while an attacker modifies the voltage measurement with the reference values. We collect datasets from a hardware platform modeled after a simplified microgrid and running the MaR attack performed with a Man-in-the-Middle (MitM) technique. We use the collected datasets to compare different attack detection algorithms based on multiple categories of machine learning algorithms. Our results show that the Random Forest algorithm outperforms the others to detect suspicious packets modified by a MitM attacker with an accuracy close to 97%.

关键词： Voltage measurement Microgrids Voltage control machine learning algorithms Control systems Communication networks Mars

来源：评论

学校读者我要写书评

暂无评论

Leukemia Diagnosis Based on machine learning algorithms

Leukemia Diagnosis Based on Machine Learning Algorithms

引用

Innovation in Technology (INOCON), IEEE International Conference for

作者： S. Patil Babaso S.K. Mishra Aparna Junnarkar Shri Venkateshwara University U.P.

ISBN: (数字)9781728197449

ISBN: (纸本)9781728197456

Leukemia is brought about by the quick generation of unusual white platelets. The high number of strange white platelets are not ready to battle contamination, and they impede the capacity of the bone marrow to create red platelets and platelets. machine learning techniques are widely used in the diagnosis and classification of different leukemia types in the patients. In this paper, we have described the different machine learning algorithms like Support Vector machines, k-Nearest Neighbour, Neural Networks, Naïve Bayes and Deep learning algorithms which are used to classify leukemia into its sub-types and presented a comparative study of these algorithms.

关键词： Classification algorithms Feature extraction Support vector machines Cells (biology) Deep learning White blood cells machine learning algorithms

来源：评论

学校读者我要写书评

暂无评论

Performance Analysis of machine learning algorithms in Credit Cards Fraud Detection

Performance Analysis of Machine Learning Algorithms in Credi...

引用

International Conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions)

作者： Vinod Jain Mayank Agrawal Anuj Kumar Department of Computer Engineering and Applications GLA University Mathura Uttar Pradesh India

ISBN: (数字)9781728170169

ISBN: (纸本)9781728170176

Credit cards are very commonly used in making online payments. In recent years' frauds are reported which are accomplished using credit cards. It is very difficult to detect and prevent the fraud which is accomplished using credit card. machine learning(ML) is an Artificial Intelligence (AI) technique which is used to solve many problems in science and engineering. In this paper, machine learning algorithms are applied on a data set of credit cards frauds and the power of three machine learning algorithms is compared to detect the frauds accomplished using credit cards. The accuracy of Random Forest machine learning algorithm is best as compared to Decision Tree and XGBOOST algorithms.

关键词： machine learning algorithms Credit cards Forestry Decision trees Prediction algorithms machine learning Classification algorithms

来源：评论

学校读者我要写书评

暂无评论

Privacy-Encoding Models for Preserving Utility of machine learning algorithms in Social Media

Privacy-Encoding Models for Preserving Utility of Machine Le...

引用

IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Sara Salim Nour Moustafa Benjamin Turnbull School of Engineering and IT University of New South Wales Canberra Australia

ISBN: (数字)9781665403924

ISBN: (纸本)9781665403931

Social media has become a vital platform in our daily life, where users can interact with their friends and other people throughout the world. The vast data generated by these platforms is unique in its variety and sensitivity, and although it potentially has significant utility, but also the potential for misuse. Although social media providers apply some existing privacy techniques, such as encryption and anonymization, the techniques cannot achieve a solid level of data privacy while maintaining the highest level of data utility. This paper proposes new Privacy-Encoding (PE) models that contain two-levels of data privacy: 1) data perturbation-based encoding techniques, and 2) data normalization-based scaling techniques. The data perturbation-based encoding techniques involve label encoder and one-hot encoder ones, while data normalization-based scaling techniques include min-max and z-score normalization ones. The aim of the two-levels is to transform original data into perturbed data, along with balancing the high level of data utility using machine learning algorithms. To evaluate the data utility, the proposed models are applied on the adult dataset as well as a simulated social media dataset and the accuracy of the results is compared with several machine learning algorithms. The experiment results reveal that the models could achieve high privacy and utility levels in terms of variance, accuracy and f-measure metrics.

关键词： Data privacy Privacy machine learning algorithms Social networking (online) Data models Encoding Numerical models

来源：评论

学校读者我要写书评

暂无评论

An Example of Performance Comparison of Supervised machine learning algorithms Before and After PCA and LDA Application: Breast Cancer Detection

An Example of Performance Comparison of Supervised Machine L...

引用

Innovations in Intelligent Systems and Applications Conference

作者： Seda Kaya Mete Yağanoğlu Bilgisayar Mühendisliği Bölümü Atatürk Üniversitesi Erzurum Türkiye

ISBN: (数字)9781728191362

ISBN: (纸本)9781728191379

Rapid and accurate diagnosis of common diseases such as breast cancer that is common among women is of great importance. While this determination is made by specialist doctors, studies are carried out with machine learning algorithms to help them. machine learning algorithms make inferences from existing data and predict what is unknown. Supervised machine learning algorithms used in classification of categorical data and of new data are frequently used in today's problems. In this study, dataset with 357 malign and 212 benign created using the features of the University of Wisconsin by making some measurements in the mass images on the breast and the feature methods extracted from these features were used. After applying the necessary pre-processing and normalization steps for the dataset, the data was separated as training and test data and training was performed for six supervised machine learning algorithms (k-nearest neighbors algorithm, random forest algorithm, decision trees, naive bayes algorithm, support vector machines and logistic regression). In addition, the same operations were carried out by applying principal components analysis and linear discriminant analysis to the dataset. In this study, the accuracy values for all our models were increased after applying linear discriminant analysis and a success rate of 96.49% was achieved with Logistic Regression. It was aimed to select the appropriate algorithm and to obtain observation that will be the source of the next studies with the result to be obtained in this study.

关键词： Principal component analysis machine learning algorithms Support vector machines Breast cancer Feature extraction Training Prediction algorithms

来源：评论

学校读者我要写书评

暂无评论

Hepatocellular Carcinoma (HCC) Liver Cancer prediction using machine learning algorithms

Hepatocellular Carcinoma (HCC) Liver Cancer prediction using...

引用

IEEE India Conference (INDICON)

作者： Sanapala Rajesh Nurul Amin Choudhury Soumen Moulik National Institute of Technology Meghalaya Shillong India

ISBN: (数字)9781728169163

ISBN: (纸本)9781728169170

In this paper, we have discussed regarding the prediction model of Hepatocellular carcinoma (HCC) liver cancer. As it is one of the most common types of liver cancer which takes the lives of thousands of people around the world, we have proposed a straight-forward approach of predicting the HCC liver cancer using publicly available dataset. Different types of data pre-processing are done on the dataset for extracting the most optimal information, and also different types of classification models (Like KNN, Decision Tree, etc.) are used in our experiment to see the prediction results. We achieved good results in terms of accuracy and computational time.

关键词： machine learning algorithms Dies Liver Predictive models Feature extraction Random forests Cancer

来源：评论

学校读者我要写书评

暂无评论

Air Quality Prediction using machine learning algorithms –A Review

Air Quality Prediction using Machine Learning Algorithms –A...

引用

International Conference on Advances in Computing, Communication Control and Networking (ICACCCN)

作者： Tanisha Madan Shrddha Sagar Deepali Virmani BPIT(GGSIPU)

ISBN: (数字)9781728183374

ISBN: (纸本)9781728183381

Predicting air quality is necessary step to be taken by government as it is becoming the major concern among the health of human beings. Air quality Index measure the quality of air. Various air pollutants causing air pollution are Carbon dioxide, Nitrogen dioxide, carbon monoxide etc that are released from burning of natural gas, coal and wood, industries, vehicles etc. Air Pollution can cause severe disease like lungs cancer, brain disease and even lead to death. machine learning algorithms helps in determining the air quality index. Various research is being done in this field but still results are still not accurate. Dataset are available from Kaggle, air quality monitoring sites and divided into two Training and Testing. machine learning algorithms employed for this are Linear Regression, Decision Tree, Random Forest, Artificial Neural Network, Support Vector machine.

关键词： Support vector machines machine learning algorithms Wood industry Prediction algorithms Air pollution Indexes Diseases

来源：评论

学校读者我要写书评

暂无评论

Effectiveness of dataset reduction in testing machine learning algorithms

Effectiveness of dataset reduction in testing machine learni...

引用

IEEE International Conference on Artificial Intelligence Testing (AITest)

作者： Jaganmohan Chandrasekaran Huadong Feng Yu Lei Raghu Kacker D. Richard Kuhn Department of Computer Science & Engineering The University of Texas at Arlington Arlington USA Information Technology Lab National Institute of Standards and Technology Gaithersburg USA

ISBN: (数字)9781728169842

ISBN: (纸本)9781728169859

Many machine learning algorithms examine large amounts of data to discover insights from hidden patterns. Testing these algorithms can be expensive and time-consuming. There is a need to speed up the testing process, especially in an agile development process, where testing is frequently performed. One approach is to replace big datasets with smaller datasets produced by random sampling. In this paper, we report a set of experiments that are designed to evaluate the effectiveness of using reduced datasets produced by random sampling for testing machine learning algorithms. In our experiments, we use as subject programs four supervised learning algorithms from the Waikato Environment for Knowledge Analysis (WEKA). We identify five datasets from *** to run with the four learning algorithms. For each dataset, we generate reduced datasets of different sizes using two random sampling strategies, i.e., pure random and stratified random sampling. We execute our subject programs with the original and the reduced datasets, and measure test effectiveness using branch and mutation coverage. Our results indicate that in most cases, reduced datasets of even very small sizes can achieve the same or similar coverage achieved by the original dataset. Furthermore, our results indicate that reduced datasets produced by the two sample strategies do not differ significantly, and branch coverage correlates with mutation coverage.

关键词： Testing machine learning algorithms Classification algorithms Forestry Clustering algorithms Training machine 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 << < 173 174 175 176 177 178 179 180 181 182 > >>

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：