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

554 篇 会议
8 册 图书
2 篇 期刊文献

馆藏范围

564 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

387 篇 工学
- 370 篇 计算机科学与技术...
- 246 篇 软件工程
- 61 篇 信息与通信工程
- 58 篇 生物工程
- 43 篇 生物医学工程（可授...
- 29 篇 电气工程
- 25 篇 控制科学与工程
- 18 篇 化学工程与技术
- 14 篇 机械工程
- 13 篇 光学工程
- 13 篇 农业工程
- 13 篇 安全科学与工程
161 篇 理学
- 106 篇 数学
- 61 篇 生物学
- 57 篇 系统科学
- 39 篇 统计学（可授理学、...
- 20 篇 物理学
- 13 篇 化学
- 9 篇 大气科学
95 篇 管理学
- 52 篇 图书情报与档案管...
- 47 篇 管理科学与工程(可...
- 24 篇 工商管理
42 篇 医学
- 42 篇 临床医学
- 41 篇 基础医学(可授医学...
- 29 篇 药学(可授医学、理...
- 15 篇 公共卫生与预防医...
18 篇 农学
- 18 篇 作物学
15 篇 法学
- 11 篇 社会学
10 篇 教育学
- 10 篇 教育学
9 篇 经济学
- 9 篇 应用经济学

主题

115 篇 machine learning
50 篇 deep learning
43 篇 machine learning...
37 篇 accuracy
35 篇 support vector m...
21 篇 predictive model...
19 篇 security
18 篇 data models
15 篇 adversarial mach...
15 篇 feature extracti...
15 篇 random forests
15 篇 prediction algor...
15 篇 training
14 篇 decision trees
14 篇 classification a...
14 篇 forecasting
13 篇 computational mo...
12 篇 internet of thin...
11 篇 information tech...
11 篇 real-time system...

机构

3 篇 faculty of compu...
2 篇 faculty of compu...
2 篇 infologia techno...
2 篇 kindi center for...
2 篇 centre of resear...
2 篇 department of co...
2 篇 graphic era hill...
2 篇 greater bay area...
2 篇 vellore institut...
2 篇 department of ar...
2 篇 school of comput...
2 篇 department of ma...
2 篇 chitkara centre ...
2 篇 fraunhofer cente...
2 篇 department of co...
2 篇 sreyas institute...
2 篇 school of comput...
2 篇 ipmi internation...
2 篇 al-farabi kazakh...
2 篇 department of ma...

作者

6 篇 azar ahmad taher
3 篇 bhatnagar roheet
3 篇 foozy cik feresa...
3 篇 ammar hossam has...
2 篇 valeeva elvira
2 篇 khan ayub
2 篇 santos igor
2 篇 varun ojha
2 篇 shreya
2 篇 bringas pablo ga...
2 篇 kurniawan r.
2 篇 maragatharajan m...
2 篇 usha g.
2 篇 singh shikha
2 篇 xiao kai
2 篇 cao peng
2 篇 shyamala devi m.
2 篇 nazri m.z.a.
2 篇 m. maragatharaja...
2 篇 swathi p.

语言

507 篇 英文
55 篇 其他
3 篇 中文

检索条件"任意字段=4th International Conference on Machine Learning and Soft Computing, ICMLSC 2020"

共 564 条记录，以下是261-270 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：

An Extreme learning machine-Based Model for Cryptocurrencies Prediction 1

引用

4th international conference on Smart computing and Informatics, SCI 2020

作者： Nayak, Sarat Chandra Satyanarayana, B. Kar, Bimal Prasad Karthik, J. CMR College of Engineering and Technology Hyderabad501401 India CMR Institute of Technology Hyderabad501401 India Gandhi Institute for Technological Advancement Bhubaneswar752054 India

ISBN: (数字)9789811608780

ISBN: (纸本)9789811608773

Cryptocurrency, in a short period of time has got wide popularity and considered as an investment asset. Prediction of cryptocurrency is a recent area of research interest and budding fast. the price trend of cryptocurrency behaves arbitrarily and fluctuates like other stock markets due to inherent volatility. though few computational intelligence methods are available, sophisticated methodologies for accurate prediction of cryptocurrency are still lacking and need to be explored. Extreme learning machine (ELM) is a faster and better learning method for neural networks with solitary hidden layer and has enhanced generalization performance. this study proposes an ELM based approach for prediction of four emerging cryptocurrencies such as Litecoin, Ethereum, Ripple, and Bitcoin. the prediction ability of the proposed approach is compared with few similar methods such as RBFN, SVM, MLP, ARIMA, and LSE. From exhaustive simulation studies and comparative result analysis it is found that the ELM method performed better than others and hence can be suggested as an efficient tool for cryptocurrencies prediction. © 2021, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Accelerated Sorting of Apples Based on machine learning 4th

Accelerated Sorting of Apples Based on Machine Learning

引用

4th international conference on Smart computing and Informatics, SCI 2020

作者： Deb, Kiron Basu, Shobhin Palakurthy, Vamshi Krishna Bhattacharyya, Nabarun Calcutta International School Kolkata India Fremont High School Sunnyvale CA United States Centre for Development of Advanced Computing Kolkata India

ISBN: (纸本)9789811608773

Accurate classification and grading are important for the quality assurance of apples since it is necessary to ensure that they retain their freshness and texture until they reach the end user following transportation and storage. We demonstrate that machine learning makes it feasible to separate high-quality apples from the poor-quality ones, which have signs of rotting, insect damage, and other forms of degradation. An alternative to the prevalent manual process of sorting and classification of apples is proposed. We focus on apples grown in orchards in Kashmir and USA. We analyze images taken following harvest using two machine learning models—an open source model as well as a well-known commercial tool. We also propose a hybrid approach for sorting perishable inventory that streamlines the process by using a high-throughput sorter based on image classification. We weed out the apples with surface blemishes in the sorting stage to identify potentially premium grade apples. the apples sorted by our approach are further screened by existing industry-standard procedures such as manual sorting or automated processes like acoustic analysis for classification into different grades. Using this two-step approach, we reduce the time for isolating the higher quality apples compared to a process that relies on a single-step sorting process only. this also achieves greater consistency and economies of scale. © 2021, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Computer vision

来源：评论

学校读者我要写书评

暂无评论

Clustering Techniques and Research Challenages in machine learning 4

Clustering Techniques and Research Challenages in Machine Le...

引用

4th international conference on computing Methodologies and Communication, ICCMC 2020

作者： Sonawane, Ritesh C. Patil, Hitendra D. S.S.V.P.S B.S.Deore College of Engineering Deopur Dhule Maharashtra424005 India

ISBN: (纸本)9781728148892

Clustering is a technique used to detect a group of similar data. Clustering is generally used for grouping the items with the similar information. Clustering always appears as an unsupervised learning technique. It appears as a common technique used for statistical data, machine learning and computer science analysis. Clustering is an unsupervised learning method that remains suitable for the investigation of interrelationships between samples to make a preliminary assessment of the sample structure. As it is very difficult for human to understand data in a high-dimensional space, clustering is employed. there are many real world applications for clustering. there are several ways to implement clustering algorithm such as centralized, distributed, connectivity, group, graph and density. Existing clustering algorithms are k-means, hierarchical, mean-shift, expectation-maximization, DBSCAN. © 2020 IEEE.

关键词： Unsupervised learning

来源：评论

学校读者我要写书评

暂无评论

Prediction of Energy Consumption Using Statistical and machine learning Methods and Analyzing the Significance of Climate and Holidays in the Demand Prediction 4th

Prediction of Energy Consumption Using Statistical and Machi...

引用

4th international conference on computing and Network Communications, CoCoNet 2020

作者： Tata, Naveen Machiraju, Srivasthasva Srinivas Akshay, V. Menon, Divyasree Mohan Sai Shibu, N.B. Arjun, D. Amrita Vishwa Vidyapeetham Amritapuri India Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (纸本)9789813369863

With the increase in the development of smart metering in energy systems, a large amount of data is being generated. the data consists of energy generated, energy consumed and energy stored with respect to time. this data can be used to improve the efficiency, reliability and stability of the power system by using machine learning algorithms. Energy requirement of each consumer can be predicted with the available data. Renewable energy generation can also be predicted. In this paper, different statistical and machine learning models are used to analyze the energy usage in smart communities. To validate the prediction models, smart meter data from our campus is used. the results show that the long short-term memory (LSTM) model is more suitable for energy demand prediction. the LSTM model is then used to predict the energy demand in students’ hostels during conditions such as climate and holidays. © 2021, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Smart power grids

来源：评论

学校读者我要写书评

暂无评论

Automatic Fake News Detector in Social Media Using machine learning and Natural Language Processing Approaches 4th

Automatic Fake News Detector in Social Media Using Machine L...

引用

4th international conference on Smart computing and Informatics, SCI 2020

作者： Srinivas, J. Venkata Subba Reddy, K. Sunny Deol, G.J. VaraPrasada Rao, P. SR University Warangal India Kallam Haranadha Reddy Institute of Technology Guntur India Gokaraju Rangaraju Institute of Technology Hyderabad India

ISBN: (纸本)9789811615016

the definition of fake news is a cooked-up story with an objective to fool or to cheat people. the current research aims to detect fake news in social media like Twitter, Watsapp and Facebook by studying the responses of the proposed model on posts acquired from Reddit online news store. Automatic fake news detection is a complex activity as it involves the model to implement natural language processing concepts in-tandem with machine learning approaches. Two feature extraction algorithms, namely CountVectoriser (CV) and term frequency-inverse document frequency (TFIDF), were employed separately for extracting the most relevant features from the dataset. these features were fed to multinomial naive Bayes (MNB), random forest (RF), support vector classifier (SVC) and logistic regression (LR) classifiers for classifying fake news creating a total of eight classification models. A solitary CV-based model was considered as the baseline model for predicting fake news in r/theonion and r/nottheonion datasets. GridsearchCV was also implemented for finding the testing and training scores for the selected parameters. Out of these models, TFIDF with MNB achieved an accuracy of 79.05% and is considered as the best. © 2021, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： machine learning

来源：评论

学校读者我要写书评

暂无评论

Proceedings of the 4th international conference on computing Methodologies and Communication, ICCMC 2020

Proceedings of the 4th International Conference on Computing...

引用

4th international conference on computing Methodologies and Communication, ICCMC 2020

ISBN: (纸本)9781728148892

the proceedings contain 195 papers. the topics discussed include: NLP based machine learning approaches for text summarization;design of novel wireless sensor network enabled IoT based smart health monitoring system for thicket of trees;a machine learning based spam detection mechanism;on the strategies for risk aware cloud and fog broker arbitrage mechanisms;sentimental analysis (opinion mining) in social network by using SVM algorithm;dynamic stability improvement using genetic algorithm tuned controllers embedded in generator control loops;a review on various data sharing strategies for privacy of cloud storage;coverless image steganography using Haar integer wavelet transform;constellation design for dual-mode OFDM-IM;and higher efficiency solar and thermal hybrid power plant based on PI controller.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A machine learning based Spam Detection Mechanism 4

A Machine Learning based Spam Detection Mechanism

引用

4th international conference on computing Methodologies and Communication, ICCMC 2020

作者： Govil, Nikhil Agarwal, Kunal Bansal, Ashi Varshney, Astha GLA University Department of CEA IET Mathura India GLA University Mathura India

ISBN: (数字)9781728148892

ISBN: (纸本)9781728148892

In today's internet-oriented data;receiving spam email messages are quite obvious. Most of the time such emails are commercial. But many times, such emails may contain some phishing links that have malware. this arises the need for proposing prudent mechanism to detect or identify such spam emails so that time and memory space of the system can be saved up to a great extent. In this paper, we presented the same mechanism which can filter spam and non-spam emails. Our proposed algorithm generates dictionary and features and trains them through machine learning for effective results. © 2020 IEEE.

关键词： Electronic mail

来源：评论

学校读者我要写书评

暂无评论

An Embedded AI computing Platform for Aircrafts Based on VPX Bus 4

An Embedded AI Computing Platform for Aircrafts Based on VPX...

引用

4th CAA international conference on Vehicular Control and Intelligence, CVCI 2020

作者： Chen, Zhinan Liu, Jingyu Zhou, Xiaobo Beijing Institute of Control and Electronic Technology Beijing China

ISBN: (纸本)9781728184968

this paper presents a VPX-based computing platform for aircrafts with an artificial intelligence module built in. VPX bus connects together a serial computing module, a parallel computing module and an AI computing module, providing all the computing resources for the platform. these modules can communicate with varying topological types through SRIO connection, with a maximum data transfer rate of 2.5Gbps. the AI module, which consists of an ARM-based CPU and a machine learning unit focusing on accelerating neural networks, has been tested to show the ability to handle ImageNet classification tasks up to 2214 frames per second when using the TensorFlow framework. © 2020 IEEE.

关键词： machine learning

来源：评论

学校读者我要写书评

暂无评论

Real-Time Driver Distraction Detection Using OpenCV and machine learning Algorithms 1

引用

4th international conference on Smart computing and Informatics, SCI 2020

作者： Swathi, V.N.V.L.S. Akhilesh, D. Senthil Kumar, G. Vathsala, A. Vani CVR College of Engineering Hyderabad India SRM Institute of Technology Chennai India

ISBN: (数字)9789811608780

ISBN: (纸本)9789811608773

Continuous driver interruption identification is the center to numerous interruption countermeasures and major for building a driver-focused driver help framework. As more remote correspondence, diversion and driver help frameworks multiply the vehicle advertise, and the rate of interruption-related accidents is relied upon height. this article presents a diagram promising methodology which is to grow continuous driver interruption countermeasures, including three categories: distraction prevention before distraction occurs;distraction mitigation after distraction occurs;collision system adjustment when a potential collision is estimated. © 2021, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Python

来源：评论

学校读者我要写书评

暂无评论

VR Classroom for Interactive and Immersive learning with Assessment of Students Comprehension 4th

VR Classroom for Interactive and Immersive Learning with As...

引用

4th international conference on computing and Network Communications, CoCoNet 2020

作者： Jaya Sudha, J.S. Nandakumar, Nandagopal Raveendran, Sarath Sandeep, Sidharth Computer Science and Engineering Sree Chitra Thirunal College of Engineering Thiruvananthapuram India Sree Chitra Thirunal College of Engineering Thiruvananthapuram India

ISBN: (纸本)9789813369764

the virtual classroom environment is created using virtual reality that enables multiple students to enter as if in a real class but with better learning environment. Conventional learning is currently limited in the current model of textbook teaching. An interactive and visual environment provided for learning enhances the rate at which the student grasps concepts. Even though many modern online teaching methods are available today, it is not possible to check whether a student is paying attention or not. Technology is evolving at a very fast rate, and this research is an apt integration of two modern technologies: machine learning and virtual reality, so as to increase the quality of education for students. A shared VR environment, optimised for learning, will be created. Students can wear a head-mounted display and select an avatar for themselves, which will be seen by other students and teachers. the VR environment is created using Unity3D software. Students will also have to wear an EEG scanner on their heads. the output of this scanner will be fed to the machine learning subpart. Neural networks are used to identify whether the student is paying attention or not. If a student is not paying attention, the teacher will be informed about it, with a message near the student’s avatar. It has many advantages over traditional learning techniques, like usage of multiple senses and inclusivity for differently abled students. © 2021, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Students

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57页 << < 23 24 25 26 27 28 29 30 31 32 > >>

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：