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

22,750 篇 会议
3,246 篇 期刊文献
19 篇 学位论文
7 册 图书

馆藏范围

26,021 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

5,179 篇 工学
- 3,111 篇 计算机科学与技术...
- 2,554 篇 电气工程
- 1,395 篇 信息与通信工程
- 691 篇 控制科学与工程
- 600 篇 软件工程
- 288 篇 仪器科学与技术
- 222 篇 环境科学与工程（可...
- 189 篇 机械工程
- 183 篇 生物医学工程（可授...
- 164 篇 交通运输工程
- 150 篇 测绘科学与技术
- 131 篇 生物工程
- 124 篇 电子科学与技术（可...
- 124 篇 石油与天然气工程
- 120 篇 材料科学与工程（可...
- 115 篇 网络空间安全
- 96 篇 土木工程
- 95 篇 动力工程及工程热...
- 65 篇 水利工程
951 篇 理学
- 290 篇 生物学
- 190 篇 物理学
- 159 篇 化学
- 139 篇 地球物理学
- 135 篇 数学
- 84 篇 系统科学
616 篇 管理学
- 529 篇 管理科学与工程(可...
- 69 篇 图书情报与档案管...
437 篇 医学
- 284 篇 临床医学
- 95 篇 基础医学(可授医学...
227 篇 农学
- 148 篇 作物学
53 篇 经济学
52 篇 法学
49 篇 文学
47 篇 教育学
17 篇 艺术学
3 篇 军事学
2 篇 哲学

主题

26,022 篇 machine learning...
8,400 篇 machine learning
4,276 篇 support vector m...
4,237 篇 accuracy
4,197 篇 prediction algor...
3,618 篇 predictive model...
3,490 篇 training
3,224 篇 classification a...
3,187 篇 feature extracti...
1,955 篇 data models
1,814 篇 computational mo...
1,787 篇 deep learning
1,684 篇 random forests
1,469 篇 neural networks
1,400 篇 real-time system...
1,399 篇 clustering algor...
1,276 篇 data mining
1,147 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
13 篇 surendran r
12 篇 qiangfu zhao
12 篇 amit kumar
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

25,809 篇 英文
155 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 26022 条记录，以下是4681-4690 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：

Analyzing Uber's data to extract valuable insights using machine learning

Analyzing Uber's data to extract valuable insights using Mac...

引用

IoT, Communication and Automation Technology (ICICAT), International Conference on

作者： Bharat Bhardwaj Himanshu Tiwari Alok Kumar Sandeep Saxena Department of Information Technology ABES Engineering College Ghaziabad India JIMS Greater Noida India Greater Noida Institute of Technology Greater Noida India

ISBN: (数字)9798350368109

ISBN: (纸本)9798350368116

Uber was founded only eleven years ago but has become one of the largest companies in the world. UberX claims to charge 30% less than taxis in Boston. This is a great way to attract customers' attention. Today, we have seen many applications of machine learning and artificial intelligence in many fields, which led us to explore their use in predicting Uber taxi prices. In this project, we conducted an experiment using real-world data to explore the use of machine learning algorithms in identifying patterns in data. We mainly focus on using machine learning algorithms to predict the price of various Uber rides. Our problem is in the regression tracking training category. We use a variety of machine learning algorithms, such as linear regression, tree pruning, random forest regressors, and gradient boosting regressors, and finally choose the algorithm that produces the most accurate cost estimates. We should choose algorithms that maximize accuracy and minimize overfitting. We have a lot of experience preparing data for the Boston Uber dataset. It is also fascinating to learn about the many factors that affect Uber ride prices.

关键词： Training machine learning algorithms Accuracy Shared transport Pricing Prediction algorithms User experience Regression tree analysis Random forests Public transportation

来源：评论

学校读者我要写书评

暂无评论

Hyperparameter-Tuned machine learning Model for the IDs Security in Cloud Environment

Hyperparameter-Tuned Machine Learning Model for the IDs Secu...

引用

Intelligent algorithms for Computational Intelligence Systems (IACIS), International Conference on

作者： Rajashekar Kandakatla K. Rajakumari Department of CSE School of Computing Bharath Institute of Higher Education and Research Chennai India Department of CSE School of Basic Sciences Bharath Institute of Higher Education and Research Chennai India

ISBN: (数字)9798350360660

ISBN: (纸本)9798350360677

In today's digitally interconnected landscape, cybersecurity remains a paramount concern as cyber-attacks continue to pose significant threats to individuals, organizations, and nations. However, traditional methods of attack classification often struggle to balance the necessity of maintaining data privacy and confidentiality with the requirement for high accuracy and robustness. In this paper, we introduce a pioneering approach to attack classification known as cryptographic hyper parameter tuning with machine learning (HT-ML). By seamlessly integrating cutting-edge cryptographic techniques, such as homomorphic encryption and Elliptic Curve Cryptography (ECC), with state-of-the-art machine learning algorithms, our methodology empowers secure and precise classification of diverse cyber-attacks within network traffic data. Through meticulous experimentation and evaluation, we showcase the efficacy and resilience of the HT-ML system in accurately identifying and categorizing attacks while upholding stringent data privacy standards. Our empirical results reveal substantial enhancements in classification performance across successive iterations of training, with notable metrics such as accuracy, precision, recall, and F1-score consistently achieving remarkable numerical values across various attack types. For instance, we observed accuracy values ranging from 95.0% to 98.9%, precision values ranging from 92.5% to 97.6%, recall values ranging from 97.5% to 99.2%, and F1-score values ranging from 94.8% to 98.0% across different iterations and attack types. Moreover, our analysis of hyper parameter optimization underscores the pivotal role of fine-tuning critical parameters in maximizing the machine learning model's effectiveness. Overall, our findings underscore the potential of HT-ML as a promising paradigm for bolstering cybersecurity defences in distributed and privacy-sensitive environments, thereby reinforcing the resilience of contemporary cybersecurity frameworks.

关键词： Training Data privacy Accuracy machine learning algorithms Telecommunication traffic Elliptic curve cryptography Distance measurement Cryptography Cyberattack Tuning

来源：评论

学校读者我要写书评

暂无评论

Application of machine learning Tools in Computer-Aided Design of Technological Processes (CAPP)

Application of Machine Learning Tools in Computer-Aided Desi...

引用

Neural Networks and Neurotechnologies (NeuroNT), II International Conference on

作者： Aleksandr A. Laptev Sergey D. Tretyakov Faculty of Control Systems and Robotics ITMO University Saint-Petersburg Russia

ISBN: (数字)9798350363739

ISBN: (纸本)9798350363746

In this work, various methods of designing technological processes are highlighted, their comparative analysis is conducted and general stages are highlighted. Special attention was paid to the analysis of solutions in the information retrieval subsystem, where the search of parts-analogues in the existing systems of automated design of technological processes (CAD TP) is realized. On the basis of the conducted analysis, a new approach to the search for parts-analogues and unification of details with the use of tools and algorithms of machine learning has been proposed. The use of a new database format in CAD TP is also proposed, which allows to significantly simplify the process of search and unification of details. And also to improve the efficiency of the search by reducing the time and qualitative results. The obtained results and proposals can become the basis for improving the process design procedure in industry and increasing the efficiency of the use of computer-aided process design systems.

关键词： Process design machine learning algorithms Databases machine learning Manuals Proposals Task analysis

来源：评论

学校读者我要写书评

暂无评论

Supplier Segmentation in Large Enterprises: A Supervised machine learning Approach

Supplier Segmentation in Large Enterprises: A Supervised Mac...

引用

IEEE International Conference on Industrial Engineering and Engineering Management

作者： Bedoor Bahameish Mohammed Yaqot Brenno Menezes Division of Engineering Management and Decision Sciences College of Science and Engineering Hamad Bin Khalifa University Doha Qatar

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

With today’s extensive outsourcing practices, the role of supplier relationship management (SRM) in supply chain management (SCM) has never been more critical. This study investigates the use of machine learning (ML) techniques to enhance supplier segmentation in large-scale enterprises (LSEs). Supervised ML algorithms, including boosting, decision trees (DT), k-nearest neighbors (KNN), random forest (RF), and support vector machines (SVM), were applied to a dataset of 32,089 purchase orders from ABC, a large-scale enterprise. The random forest algorithm demonstrated the highest performance, with an AUC score of $\mathbf{9 9. 6 \%}$ and precision of $\mathbf{9 7. 8 \%}$, indicating its robustness for supplier classification. The study’s key findings underscore how ML-driven segmentation improves procurement decision-making, enabling more accurate supplier categorization, which in turn optimizes resource allocation and strengthens SRM practices. These insights position ABC as a leader in adopting ML for supply chain management, offering a scalable and efficient solution to supplier segmentation.

关键词： Support vector machines Procurement Radio frequency machine learning algorithms Accuracy Standards organizations Organizations Nearest neighbor methods Data models Random forests

来源：评论

学校读者我要写书评

暂无评论

Two Stage machine learning Framework to Identify Periodontitis and Dental Caries

Two Stage Machine Learning Framework to Identify Periodontit...

引用

Mobile Networks and Wireless Communications (ICMNWC), IEEE International Conference on

作者： R. Kausalya J. Anitha Ruth Department of Computer Science and Applications SRM Institute of Science and Technology Chennai India

ISBN: (数字)9798331528348

ISBN: (纸本)9798331528355

Background: Detecting dental caries and periodontitis through X-ray images is challenging due to image variability, overlapping anatomical structures, and subtle early-stage symptoms. Early diagnosis is essential for preventing disease progression and maintaining oral health. Methods: This research proposes a two-stage machine learning system for automatic and precise dental disorder diagnosis. The X-ray images are preprocessed and segmented using the fuzzy C-means clustering algorithm (FCM) to isolate regions of interest (ROI). Textural features are extracted via the Grey Level Co-occurrence Matrix (GLCM). A Support Vector machine (SVM) classifier is used to classify the images into healthy or unhealthy, and further categorize unhealthy images into periodontitis, dental caries, and other dental conditions. Results: The proposed model achieved diagnostic accuracies of 98.8%, 98.5%, and 98.2% for different classes, demonstrating its high performance. Concluding Remarks: The proposed framework proves to be a reliable tool for enhancing clinical diagnoses and automating dental disease detection.

关键词： Support vector machines machine learning algorithms Accuracy Clustering algorithms Teeth Feature extraction Dentistry Classification algorithms X-ray imaging Diseases

来源：评论

学校读者我要写书评

暂无评论

Evaluation of machine-learning Based Approaches for Early Detection of Breast Cancer Tumor

Evaluation of Machine-Learning Based Approaches for Early De...

引用

International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)

作者： Fares Mohammad Bader Al-Haran Iyad Abu Doush Marwa Kandil College of Engineering and Applied Science American University of Kuwait Kuwait Kuwait Computer Science Department Yarmouk University Irbid Jordan

ISBN: (数字)9798331533137

ISBN: (纸本)9798331533144

Chances of survival can be significantly improved through early detection of breast cancer. Traditional breast cancer detection techniques require experts to identify the physical features of breast tumors from medical tests. However, the limited number of medical experts will leave many women at risk of developing higher stages of cancer. Large amount of data can be efficiently analysed using machine learning (ML) algorithms to recognise abnormal patterns; thus providing an early detection tool for breast cancer. This paper examines the outcome of six distinct ML algorithms in classifying breast tumors to either benign tumor (B), or malignant tumor (M). The models of ML utilized Wisconsin Breast cancer dataset that contains 569 rows of data and 32 features for training. The models were evaluated by the ROC curve, the confusion matrix, precision, recall, accuracy, and Fl score values. The ex-perimental results proved that SVM and KNN models achieved the highest accuracy of 98.24 %, and Fl score of 98 % for SVM and 99% for KNN. This indicates that SVM and KNN models handled the data's complexity effectively and performed accurate prediction of breast tumor type.

关键词： Support vector machines Breast tumors Accuracy machine learning algorithms Malignant tumors Benign tumors machine learning Nearest neighbor methods Breast cancer Classification algorithms

来源：评论

学校读者我要写书评

暂无评论

Multi-Agent Model-Based Deep Reinforcement learning: Testing the Method in Grid-World Environments

Multi-Agent Model-Based Deep Reinforcement Learning: Testing...

引用

International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Vladimir V. Bazhenov Department of Informatics and Control Systems Bauman Moscow State Technical University Moscow Russian Federation

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

This paper investigates the identification and resolution of social dilemmas in multi-agent reinforcement learning. The model of multi-agent environment was developed to simulate agent movement within grid-world scenarios. The study focuses on the MiniGrid and MultiGrid environments and proposes a method for multi-agent model-based reinforcement learning in these settings. The method was tested in comparison with value-based Q-learning, Deep Q-Network (DQN), Independent Q-Network (IQN), and Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithms. Experimental results demonstrate the effectiveness of the proposed approach in multi-agent grid-world environments.

关键词： Training Analytical models Power engineering Q-learning machine learning algorithms Markov decision processes Stochastic processes Games Deep reinforcement learning Testing

来源：评论

学校读者我要写书评

暂无评论

Review of machine learning in Baseball Analytics for Performance Improvement and Future Directions

Review of Machine Learning in Baseball Analytics for Perform...

引用

IEEE Southeastcon

作者： Daniel D. Wu Yu-Hsiang John Huang Jenq-Foung Yao Department of IS&CS Georgia College & State University Milledgeville Georgia U.S.A.

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

The application of machine learning (ML) in baseball analytics has revolutionized the way teams and players approach performance improvement. This literature review explores the intersection of ML and baseball analytics, focusing on key areas such as player evaluation, injury prevention, game strategy, and skill development. Highlighting advancements in data collection, algorithmic approaches, and real-world applications, this review synthesizes findings from existing research to identify trends, challenges, and opportunities for future innovation.

关键词： Technological innovation Sequential analysis machine learning algorithms Shape Prevention and mitigation machine learning Market research Injuries Sports Systematic literature review

来源：评论

学校读者我要写书评

暂无评论

Epileptic Seizure Detection from EEG: Targeting Specific Brain Regions with machine learning Approaches

Epileptic Seizure Detection from EEG: Targeting Specific Bra...

引用

International Conference on Electrical, Computer and Communication Engineering (ECCE)

作者： Mohammad Mostakim Md. Emdadul Haque Maruf Diba Das Md. Fazlul Karim Khondakar Mehdi Hasan Chowdhury Aditta Chowdhury Dept. of Electrical and Electronic Engineering Chittagong University of Engineering & Technology Chittagong Bangladesh Dept. of Biomedical Engineering Chittagong University of Engineering & Technology Chittagong Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

The electroencephalogram (EEG) signal plays a vital role in diagnosing epilepsy. The EEG recordings of the ambulatory recording systems generate very lengthy data, and the detection of epileptic activity requires an expert to analyze the entire length of the EEG data. The traditional methods of analysis being tedious, many automated diagnostic systems for epilepsy have emerged in recent years. This study aims to determine the most effective brain region in seizure detection so that the use of unnecessary electrodes and other time-consuming analyses can be reduced. Data from three distinct brain regions-central, frontal, and occipital are utilized. The denoised EEG signals are utilized to extract the time domain, frequency domain, and entropy-based features. Later, the features are used to develop machine learning algorithms for classifying the signals. Upon analysis with different combinations of features, the best accuracy has been achieved from the frontal region of the brain using the boosted tree algorithm with an accuracy of 83.5%. This approach leverages the diverse information provided by each region to enhance detection reliability. In the future, further analysis can be done targeting the frontal region for improving the performance.

关键词： Electrodes Accuracy machine learning algorithms Fast Fourier transforms Epilepsy machine learning Feature extraction Brain modeling Electroencephalography Recording

来源：评论

学校读者我要写书评

暂无评论

Leveraging machine learning to Enhance Crime Prediction and Community Safety

Leveraging Machine Learning to Enhance Crime Prediction and ...

引用

International Conference on ent Computing and Control Systems (ICICCS)

作者： S. Jancy Gunda Venkata Vamsi Krishna Gurrampati Ajith Reddy Dept. of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai Tamilnadu India

ISBN: (数字)9798331512088

ISBN: (纸本)9798331512095

Understanding crime patterns is essential for effectively addressing criminal behavior. The study analyzes crime data from Indore, publicly available on the Indore Police website, to generate predictions for the types of crimes likely to occur at specific times and locations within the city. The study employs AI and machine learning algorithms to investigate their efficacy in crime prediction, as these technologies have demonstrated success in audio and visual-based crime detection. Such systems have challenges demonstrating their dependability to legal authorities, mainly when employed for event prevention objectives. The research addresses classification issues by categorizing diverse crime types into generalized classifications, enhancing classification systems' significance and practical utility. This study evaluates various machine learning classifiers to identify the optimal classification approach and demonstrates the impact of our results. The study illustrates the capabilities of an AI-driven crime prediction system and offers ideas for improving crime prevention strategies through future research.

关键词： machine learning algorithms Law enforcement Computational modeling Scalability Prevention and mitigation Urban areas Predictive models Prediction algorithms Data models Computational efficiency

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 << < 465 466 467 468 469 470 471 472 473 474 > >>

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：