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

799 篇 会议
10 册 图书
2 篇 期刊文献

馆藏范围

811 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

539 篇 工学
- 513 篇 计算机科学与技术...
- 338 篇 软件工程
- 155 篇 信息与通信工程
- 117 篇 控制科学与工程
- 93 篇 生物工程
- 92 篇 网络空间安全
- 85 篇 石油与天然气工程
- 54 篇 生物医学工程（可授...
- 41 篇 电气工程
- 27 篇 光学工程
- 23 篇 农业工程
- 19 篇 机械工程
- 18 篇 化学工程与技术
- 17 篇 安全科学与工程
298 篇 理学
- 207 篇 数学
- 102 篇 生物学
- 65 篇 统计学（可授理学、...
- 48 篇 系统科学
- 39 篇 物理学
- 17 篇 化学
185 篇 管理学
- 136 篇 管理科学与工程(可...
- 57 篇 图书情报与档案管...
- 36 篇 工商管理
58 篇 医学
- 58 篇 基础医学(可授医学...
- 58 篇 临床医学
- 39 篇 药学(可授医学、理...
- 23 篇 公共卫生与预防医...
27 篇 法学
- 21 篇 社会学
26 篇 农学
- 26 篇 作物学
16 篇 经济学
- 16 篇 应用经济学
8 篇 教育学

主题

146 篇 machine learning
72 篇 deep learning
38 篇 machine learning...
36 篇 support vector m...
30 篇 adversarial mach...
23 篇 computational mo...
20 篇 training
19 篇 forecasting
16 篇 predictive model...
16 篇 prediction algor...
13 篇 internet of thin...
13 篇 sentiment analys...
13 篇 artificial intel...
13 篇 convolutional ne...
12 篇 object detection
11 篇 neural networks
11 篇 feature extracti...
10 篇 face recognition
10 篇 decision trees
9 篇 random forest

机构

17 篇 chitkara univers...
6 篇 pimpri chinchwad...
6 篇 univ johannesbur...
5 篇 pimpri chinchwad...
5 篇 faculty of infor...
5 篇 key lab complex ...
5 篇 baoji univ arts ...
4 篇 dept. of compute...
4 篇 department of co...
4 篇 qiannan normal u...
4 篇 department of co...
4 篇 univ witwatersra...
4 篇 department of co...
4 篇 karpagam academy...
4 篇 computer science...
3 篇 university of sa...
3 篇 amrita school of...
3 篇 department of cs...
3 篇 department of el...
3 篇 easwari engineer...

作者

7 篇 reza ahmed wasif
5 篇 s abhishek
5 篇 goyal s.b.
5 篇 jennifer sanjeda...
4 篇 anjali t.
4 篇 abhishek s.
4 篇 van zyl terence ...
3 篇 andersson karl
3 篇 chohan jasgurpre...
3 篇 swain debabrata
3 篇 singh balbir
3 篇 sha akhbar
3 篇 pawar rajendra
3 篇 shamim mahbub ha...
3 篇 shanmugasundar g...
3 篇 kukreja vinay
3 篇 tawfik hissam
3 篇 akhbar sha
3 篇 zhou jincheng
3 篇 kalita kanak

语言

739 篇 英文
72 篇 其他

检索条件"任意字段=7th International Conference on Machine Learning and Soft Computing, ICMLSC 2023"

共 811 条记录，以下是491-500 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：

machine learning Algorithms based Student Performance Prediction based on Previous Records

Machine Learning Algorithms based Student Performance Predic...

引用

international conference on computing Methodologies and Communication (ICCMC)

作者： Sreeramaneni Chandrahasa Sonti Meghala Sri Ganeshan Rahul Chowdary Maddineni Mellampudi Sai Divya Praveen Tumuluru Bulla Suneetha Department of CSE Koneru Lakshmaiah Education Foundation Vaddeswaram AP INDIA

Predicting a student's grade has become increasingly important in order to determine whether or not the student will be placed In order to develop after this and obtain better placements, it is also being attempted to ascertain the student performance. Based on their recent and prior performances, the prediction will be made. the major goal is to improve the student unsatisfactory performances so that they can improve their academic performance. Here, some of the factors are derived from academics and others from placement exams. therefore, using these factors, the predictor will determine whether or not the student will be hired by the company. the biggest problem in this situation is deciding which algorithm to utilize because there are numerous classification algorithm strategies that can be applied Based on the dataset, different algorithms produce different degrees of accuracy. the algorithms used in this article are supervised machine learning algorithms called Bayesian classification. It uses a classification method for machine learning. It is a theory that uses probability to identify a fix for the existing issue.

关键词： machine learning algorithms Computational modeling machine learning Companies Predictive models Filtering algorithms Prediction algorithms

来源：评论

学校读者我要写书评

暂无评论

A Novel machine learning based Driving Decision Strategy

A Novel Machine Learning based Driving Decision Strategy

引用

international conference on ent computing and Control Systems (ICICCS)

作者： P Sahithi V Sravanthi V.G Vanetha D Krishna Reddy Dept. of CSE VR Siddhartha Engineering College Vijayawada India

For determining the driving strategy, modern cars are solely dependent on different factors such as people and road conditions. In particular, in the case of self-driving cars that travel autonomously towards the destination, it needs to perform various repetitive identification, judgement, and control operations. To address this challenges, this research study has designed and developed an advanced driving decision strategy by assessing both its internal and exterior components (consumable conditions, Rotation Per Minute levels, and so on) with the help of machine learning models. this will reduce in-vehicle computing and achieve the most effective decision by utilizing evolutionary algorithms, past storage data and huge real-time data generated while driving a car. the data saved in the cloud are assessed by the machine learning algorithms, which then select the best driving strategy. To perform these operations, this study uses gradient boost algorithm. the research result shows that the vehicle features have a substantial influence in making a driving decision.

关键词：

来源：评论

学校读者我要写书评

暂无评论

VTAG: Virtual Lab for Tree-Adjoining Grammar-Based Research 7th

VTAG: Virtual Lab for Tree-Adjoining Grammar-Based Research

引用

7th international conference on Information and Communication Technology for Competitive Strategies , ICTCS 2022

作者： Kurariya, Pavan Chaudhary, Prashant Bodhankar, Jahnavi Singh, Lenali Kumar, Ajai Darbari, Hemant Centre for Development of Advanced Computing Pune India

ISBN: (纸本)9789811996375

this paper presents a state-of-the-art virtual research lab (vTAG) for creating, updating, analyzing, and maintaining multilingual large-scale tree-adjoining grammar for natural languages (NL). vTAG has designed to be language independent and tested its performance by constructing grammar of many Indian and European languages with significant reductions in grammar development time by auto rule creation mechanism with the help of a supervised machine learning algorithm. vTAG provides an integrated development environment (IDE) that can generate grammar of any natural language based on tree-adjoining grammar (TAG) formalism by using a specially designed graphical user interface without focusing on the programming aspect. vTAG also contains an advanced age experimental workspace to evaluate and improvise TAG-based parsers, part-of-speech tagger, sematic text analyzer, and associated NLP tools. vTAG can be utilized as an ‘interactive training kit’ for upcoming young talent to empower them for learning and developing advanced tools solving practical problems in NLP field. Furthermore, it can serve as foundation for understanding and building end-to-end machine translation solutions. vTAG uses object oriented model (OOM) for handling the NLP resources so every entity within the environment is in form of an object that can be encrypted which makes linguistic resources convenient for maintenance and secure to exchange and distribution, thus vTAG consists of a workbench, development kit, a graphical user interface, experimental workspace, and language resources on a single platform by combining major concepts from modern computer science, artificial intelligence, and linguistics. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： learning algorithms

来源：评论

学校读者我要写书评

暂无评论

Sentimental Analysis on Twitter Data using Supervised Algorithms

Sentimental Analysis on Twitter Data using Supervised Algori...

引用

international conference on computing Methodologies and Communication (ICCMC)

作者： C. Susmitha L. Nikhil L. Akhil M. Kavitha V. Surya Narayana Reddy K. Shailaja Department of CSE Koneru Lakshmaiah Education Foundation Vaddeswaram AP India Department of CSE VNR Vignana Jyothi Institute of Engineering and Technology Hyderabad Department of CSE Vasavi College of Engineering Ibrahimbag Hyderabad

Sentimental Analytics is the phenomenon used to show the feelings of different people, emotions, opinions. It is also referred as the opinion meaning, which identifies the emotional tone behind a body of text the Mechanism gives whether the result is positive, negative, or neutral. It gives finer results, to keep track of users, and tells whether the tweet is uplifted or down lifted by the user's content. machine learning can be analyzed by using various analysis algorithms to provide a precise value. machine learning algorithms play a major role in various domains, and one of them includes data analysis. In this work, machine learning techniques are used to predict the Twitter analysis. machine learning (ML) algorithms such as Support Vector machine (SVM), Logistic Regression (LR), and Naive Bayes (NB) algorithm are used for implementation. the performance of the implemented algorithm is analyzed in the terms of accuracy, precision, recall, F1-score on the tweets taken from the social media.

关键词： Support vector machines Measurement machine learning algorithms Data analysis Social networking (online) Blogs machine learning

来源：评论

学校读者我要写书评

暂无评论

A Medical Model Built on machine learning to Evaluating the Relationship between the Depression and Living Standards

A Medical Model Built on Machine Learning to Evaluating the ...

引用

international conference on computing Methodologies and Communication (ICCMC)

作者： Suggala PragnaSri Venkata Ramana Gupta Nallagattla Shaik Ajajunnisa Amarendra K Pinninti Bhanu Phanindra Sriram Parvathaneni Department Of Computer Science and Engineering Prasad V Potluri Siddhartha Institute Of Technology Vijayawada India Department Of Computer Science and Engineering Koneru Lakshmaiah Foundation Vaddeswaram Andhra Pradesh India

Future healthcare reforms are being influenced by new technological developments. Finding the elements that contribute to depression may inspire fresh research and therapeutic approaches. Depression is a difficulty that many people experience, because depression is a condition that is increasingly posing a major community health threat. To manage and analyze the diverse data and comprehend the relationship between depression and life satisfaction, this paper uses machine learning techniques. the assessment study is afterwards divided principally in to the two parts. A data consolidation procedure is introduced in the first section. Data relationships are established and each relationship in data is uniquely identified using the Secure Hash Algorithm idea. A model that incorporated was proposed in the second segment. Unsupervised machine learning technique. K-Means is used for clustering. Supervised machine learning algorithms like Naive Bayes, Multi Class Support Vector machine with Posterior Probability (MCSVMPP), KNN and Voting classifier is used to find the depression according to different factors.

关键词： Support vector machines Q-factor machine learning algorithms Computational modeling Medical services machine learning Mental health

来源：评论

学校读者我要写书评

暂无评论

An Improved System for Brain Pathology Classification using Hybrid Deep learning Algorithm

An Improved System for Brain Pathology Classification using ...

引用

international conference on computing Methodologies and Communication (ICCMC)

作者： V. Sathya S. Dhanabal Department of Computer Science and Engineering Kongunadu College of Engineering and Technology (Autonomous) Trichy India

Speech, recognizing, learning, programming, and problem-solving are all meant to be included in artificial intelligence computing activities. Artificial intelligence (AI), a subfield of computer engineering, is concerned with developing sophisticated software or technologies that act and function like human. Deep learning, a category of algorithms used in deep learning, is based on learning data representations and is one of many machine learning techniques. Deep learning is used to develop brain tumour screening and classification models for rapid and uncomplicated tumour identification using Magnetic Resonance Images (MRI) imaging. this paper shows how the pretrained model Alexnet with Transfer learning (TL) may be trained on tiny and innovative fresh data for classification problems using the stochastic-gradient descent with momentum-SGDM optimizer. Numerous hybrid models were presented with the aim of classifying a brain tumour MR image as a benign as well as malignant tumour. the accuracy, error rate, and confusion matrix parameter of the suggested models are evaluated in order to show how the works have improve.

关键词： Deep learning machine learning algorithms Error analysis Magnetic resonance imaging Computational modeling Transfer learning Speech recognition

来源：评论

学校读者我要写书评

暂无评论

Soil Nutrient Analysis for the Cultivation of Plants using machine learning Algorithms

Soil Nutrient Analysis for the Cultivation of Plants using M...

引用

international conference on ent computing and Control Systems (ICICCS)

作者： S Vidhya. R Rajalakshmi. M Mahalingamuthuram. C Mukesh. K Mohit. Department of Electronics and Communication Engineering Sri Ramakrishna Engineering College Coimbatore India Department of Information Technology Sri Ramakrishna Engineering College Coimbatore India

the machine learning algorithm is used to analyze the minerals of the soil to identify which plants to be cultivated on the specific land. In proposed work, Combining the Random Forest and Support Vector machine algorithms namely, multi-model approach. this approach helps to get an adequate information about which plant can be grown on basis of nature of the soil. the multi-model approach improved the prediction accuracy, especially when certain categories of nutrients were selected for classification. the proposed method is going to explore the different levels of nutrient characterization, ranging from 3 to 13 levels to get more precise nutritional information. this approach is highly beneficial for farmers to develop better harvests.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Multiple Disease Prediction Using machine learning Algorithm

Multiple Disease Prediction Using Machine Learning Algorithm

引用

international conference on computing Communication Control and Automation (ICCUBEA)

作者： Sahil Chaudhari Prathamesh Deo Purvaja Deshmukh Aman Deshpande Priya Shelke Abhijit Chitre Department of Information Technology VIIT Pune India Department of E&TC VIIT Pune India

Using machine learning techniques like Logistic Regression, the Support Vector machine i.e. (SVM) classifiers, the Random Forest classifiers i.e. (RFC), the Decision Tree classifiers i.e. (DTC), and K-Nearest Neighbor (KNN), as well as basic metrics like heart rate, blood pressure, cholesterol, and pulse rate, the goal of this project is to forecast the occurrence of various diseases like diabetes, heart disease, and Parkinson's disease. the most accurate calculation is used to train the dataset, while Python pickling and streamlit are used to record the model behavior. By entering pertinent disease-related information, the initiative seeks to determine the risk factors for the diseases and provide users a prognosis of whether they have the condition or not. this program can assist people in keeping an eye on their health and taking the necessary actions to prolong

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Statistical machine learning Approach to Optimize Workload in Cloud Data Centre

A Statistical Machine Learning Approach to Optimize Workload...

引用

international conference on computing Methodologies and Communication (ICCMC)

作者： Pranjal Upadhyay Krishna Kumar Sharma Rishu Dwivedi Pradeep Jha Rashtriya Raksha University Gandhinagar Gujrat India Learn and Build by TechiNest Pvt. Ltd. Jaipur Rajasthan India Department of CSE Global Institute of Technology Jaipur Rajasthan India

the modern data centre (DC) is a perplexing amalgamation of various mechanical, electrical, and control frameworks. the increasing number of possible working configurations and nonlinear interdependencies make it difficult to comprehend. To improve Data Center performance and execution, the neural network scheme can benefit from the genuinely active data. machine learning (ML) is emerging as the most suitable method of demonstrating DC execution and improving productivity by utilizing the existing sensor data. the data centre infrastructure, the tasks to be completed, and the desired profits are framed as a mathematical programming model, which can then be overcome by using alternative methods of searching for smart task programming. this paper proposes a novel method for maximizing the load on cloud infrastructure. this article has utilized the machine learning techniques to enhance the load balancing. the new proposed algorithm is evaluated and then compared against existing algorithms for analyzing the make span time, time taken to execute tasks, overall load on the virtual machines and total cluster utilization.

关键词： Productivity Data centers Cloud computing machine learning algorithms Clustering algorithms machine learning Programming

来源：评论

学校读者我要写书评

暂无评论

Improved AODV Routing Protocol Development and Analysis for Enhanced Network Performance in MANETs Based on machine learning Model 7th

Improved AODV Routing Protocol Development and Analysis for ...

引用

7th international conference on soft computing and Signal Processing, ICSCSP 2024

作者： Rao, Puttamraju Srinivasa Sreekanth, Danda Vishnu Murthy, S. Chalapathi Rao, Tippana Narasaraopeta Engineering College Andhra Pradesh Narasaraopet India Aditya Institute of Technology and Management Andhra Pradesh Tekkali India

ISBN: (纸本)9789819799251

Self-configurable and nondemobilizable wireless ad hoc networks are called MANETs. A number of security threats are present on the route because of its flexibility. In order to address this, the IDS’s performance should be changed. the machine learning (ML) technique is used in this study to provide a method for enhancing the accuracy and detection rate of the intrusion detection system (IDS) for the AODV routing protocol. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Network intrusion

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82页 << < 46 47 48 49 50 51 52 53 54 55 > >>

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：