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

23,359 篇 会议
2,934 篇 期刊文献
16 篇 学位论文

馆藏范围

26,309 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

5,648 篇 工学
- 3,392 篇 计算机科学与技术...
- 3,142 篇 电气工程
- 1,808 篇 信息与通信工程
- 640 篇 控制科学与工程
- 538 篇 软件工程
- 481 篇 仪器科学与技术
- 300 篇 机械工程
- 300 篇 测绘科学与技术
- 284 篇 生物医学工程（可授...
- 148 篇 电子科学与技术（可...
- 114 篇 生物工程
- 108 篇 交通运输工程
- 107 篇 环境科学与工程（可...
- 75 篇 网络空间安全
- 56 篇 航空宇航科学与技...
- 43 篇 材料科学与工程（可...
841 篇 理学
- 194 篇 物理学
- 158 篇 生物学
- 137 篇 地球物理学
- 124 篇 数学
- 122 篇 系统科学
- 96 篇 地理学
- 50 篇 化学
- 42 篇 统计学（可授理学、...
526 篇 管理学
- 481 篇 管理科学与工程(可...
493 篇 医学
- 369 篇 临床医学
- 100 篇 基础医学(可授医学...
195 篇 农学
- 99 篇 作物学
- 80 篇 农业资源与环境
75 篇 文学
- 70 篇 新闻传播学
23 篇 教育学
21 篇 经济学
19 篇 艺术学
13 篇 法学
7 篇 军事学
2 篇 历史学

主题

26,309 篇 classification a...
6,463 篇 feature extracti...
5,177 篇 training
4,677 篇 accuracy
4,372 篇 support vector m...
3,194 篇 machine learning...
2,671 篇 prediction algor...
2,638 篇 clustering algor...
2,490 篇 algorithm design...
2,350 篇 data mining
2,253 篇 machine learning
1,593 篇 data models
1,402 篇 deep learning
1,358 篇 optimization
1,338 篇 decision trees
1,172 篇 predictive model...
1,164 篇 testing
1,138 篇 computational mo...
1,094 篇 neural networks
1,020 篇 databases

机构

63 篇 chitkara univers...
23 篇 centre of resear...
23 篇 college of infor...
19 篇 school of comput...
18 篇 tsinghua univers...
18 篇 university of ch...
17 篇 chitkara centre ...
17 篇 school of inform...
17 篇 department of co...
16 篇 school of comput...
16 篇 school of comput...
16 篇 school of electr...
14 篇 computer science...
14 篇 univ chinese aca...
14 篇 microsoft resear...
14 篇 school of comput...
13 篇 school of electr...
13 篇 school of electr...
13 篇 school of comput...
12 篇 department of in...

作者

29 篇 wei li
22 篇 hui wang
22 篇 jun wang
21 篇 lei wang
17 篇 xia sun
17 篇 yang yang
16 篇 jing zhang
15 篇 jun zhang
15 篇 liu yang
14 篇 xi chen
14 篇 li zhang
14 篇 jie li
13 篇 jian wang
13 篇 rakesh kumar
13 篇 jie yang
13 篇 jun shi
13 篇 chen chen
12 篇 bing xue
12 篇 ahmad jalal
12 篇 xuegang hu

语言

26,172 篇 英文
91 篇 其他
33 篇 中文
4 篇 土耳其文
2 篇 法文
1 篇 西班牙文
1 篇 俄文

检索条件"主题词=Classification Algorithms"

共 26309 条记录，以下是4791-4800 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：

Collaborative Random Forests Learning 23

Collaborative Random Forests Learning

引用

23rd IEEE International Conference on High Performance Computing and Communications, 7th IEEE International Conference on Data Science and Systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Foucade, Yohan Bennani, Younes Aabbou, Zakaria LIPN-CNRS Umr 7030 Université Sorbonne Paris Nord LaMSN La Maison des Sciences Numèriques France

ISBN: (纸本)9781665494571

Collaborative learning is an emerging field of machine learning. In this framework, multiple learning algorithms try to learn from a distributed database. The main idea is to improve the performance of each algorithm by exchanging information about the local structures of the data, without disclosing sensitive information. It is related to ensemble learning and federated learning. In this work, we presents a collaborative supervised learning approach. We used classification trees as a base algorithm, although the framework is generic and could be implemented with a wide class of algorithms. The process is divided into two steps: a local and a collaboration step. The local step uses a classical supervised learning algorithm, locally and independently on each dataset, which will result in obtaining multiple classifiers for each of those bases. During the collaboration step, each algorithm will collaborate with its remote counterparts. Our approach has been tested on several datasets and has shown promising results. © 2021 IEEE.

关键词： Machine learning algorithms Smart cities Supervised learning Collaboration Distributed databases Collaborative work classification algorithms

来源：评论

学校读者我要写书评

暂无评论

A Road map for Age and Gender classification using EL-Methods

A Road map for Age and Gender Classification using EL-Method...

引用

Recent Advances in Information Technology for Sustainable Development (ICRAIS), International Conference on

作者： K. Prakash M. Sudharsan G Meenakashi Margaret Marry T Department of Computer Science Krist Jayanti College Autonomous Bengaluru Karnataka Department of Computer Science Kristu Jayanti College Autonomous Bengaluru Karnataka Department of Computer Science Justice Basheer Ahmed Sayeed College for Women Chennai Tamilnadu

ISBN: (数字)9798350354461

ISBN: (纸本)9798350354522

Age and Gender analysis is very crucial to prediction for blind people. This variety of predictions is particularly used for blind people. Gender and age classification relies on distinct attributes for their determination. The gender classification with the help of facial expression features, height, and body shape. Similarly, age classification is performed with the help of wrinkles, skin texture, and facial features. Different ML method are used to predict gender and age classification. In this work put forward, an EL-based machine learning algorithm is in use to anticipate and age classification. The SVM algorithm is used for the grouping of gender and age grouping. Based on the boosting ensemble learning with the help of SVM, performed better classification of age and genderprediction. This novelty method has been incorporated into ensemble learning with implemented using 1056 images with different pixel intensity values after prepossessing all images get into the same, and based on that, training and testing are evaluated at 80% and 20%. The proposed ensemble method produced better accuracy of age (97%) and gender (96%) grouping.

关键词： Training Support vector machines Biometrics Machine learning algorithms Accuracy Computational modeling Prediction algorithms classification algorithms Ensemble learning Testing

来源：评论

学校读者我要写书评

暂无评论

classification and recognition of ballistic microcephalus based on deep neural network

Classification and recognition of ballistic microcephalus ba...

引用

International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Tiantian Cai Yijun Sheng Zi He Wenfeng Sun School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing China National Key Laboratory of Science and Technology on space Microware Xian China

ISBN: (数字)9780996007894

ISBN: (纸本)9781728146331

To solve the problem of indistinguishable noncooperative targets and different types of micromotion in the space, the electromagnetic scattering cross-sectional area (RCS) sequence of the target to be detected was obtained by radar measurement, and the classification and identification of multiple targets with same shapes and different types of fretting form was conducted by deep neural network, and the recognition rate is higher. Firstly, a series of RCS characteristics such as mean value and period are extracted according to the target electromagnetic scattering cross-sectional area (RCS) sequence. These features are used as input of neural network classifier, and BP neural network algorithm is used to classify these targets. The experimental results show that the method based on multi-layer neural network has higher recognition rate than single-layer network, and it can improve the recognition rate of warheads with different types of fretting greatly.

关键词： Feature extraction Target recognition Biological neural networks Radar cross-sections classification algorithms

来源：评论

学校读者我要写书评

暂无评论

classification of Cognitive Activities EEGs via Singular Spectrum Analysis and Joint Approximate Diagonalization of Eigen-Matrices Algorithm with Ensemble Classifier

Classification of Cognitive Activities EEGs via Singular Spe...

引用

IEEE Symposium on Product Compliance Engineering - Asia (ISPCE-CN)

作者： Xiangyu Luo Bingo Wing-Kuen Ling Faculty of Information Engineering Guangdong University of Technology Guangzhou China

ISBN: (数字)9798331523008

ISBN: (纸本)9798331523015

Cognition involves the recognition and perception of external objects to solve creative problems and adapt to the environment, forming the foundation of human intelligence. However, neurodegenerative diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD) lead to cognitive impairment. Transcutaneous electrical nerve stimulation (TENS) is a recognized therapy for enhancing cognitive performance. This paper proposes using singular spectrum analysis (SSA) and the joint approximate diagonalization of eigen-matrices (JADE) algorithm with an ensemble classifier to classify electroencephalograms (EEGs) before and after TENS application during various cognitive activities. Initially, subjects wear a headband to acquire single-channel EEGs before and after TENS is applied to their radial nerves. Empirical mode decomposition (EMD) is then used to suppress underlying EEG trends. Subsequently, SSA and the JADE algorithm perform blind source separation (BSS) of EEGs from electromyograms (EMGs) and electrocardiograms (ECGs). JADE is a fourth-order based independent component analysis (ICA) algorithm. The tunable Q-factor wavelet transform (TQWT) decomposes EEGs into subbands from which features are extracted. Finally, an ensemble classifier, combining random forest and least squares support vector machine (LS-SVM), classifies the data. The computer numerical simulation results demonstrate that our proposed method achieves higher classification accuracy compared to existing methods.

关键词： Support vector machines Q-factor Accuracy Approximation algorithms Feature extraction Electroencephalography Blind source separation classification algorithms Random forests Spectral analysis

来源：评论

学校读者我要写书评

暂无评论

Soft set and Fuzzy Rules Enabled SVM Approach for Heart Attack Risk classification Among Adolescents

Soft set and Fuzzy Rules Enabled SVM Approach for Heart Atta...

引用

International Conference on Computing Communication Control and Automation (ICCUBEA)

作者： C. M Chethan Malode K. Bhargavi B. G Gunasheela G. Kavana R. Sushmitha Department of Information Science and Engineering Siddaganga Institute of Technology Tumkur Karnataka India

ISBN: (纸本)9781538652589;9781538652572

Nowadays heart attack is becoming more common among adolescents due to several reasons like heavy work pressure, lack of physical activities, irregular food habits, obesity, eating high fat food, smoking, sedentary life style, heavy drinking and so on. It has been reported that above ten lakh adolescents die every year due to heart related diseases. In literature maximum number of works have been carried out to address heart attack problem among old age people, however there are very less works concentrating on the heart attack detection focusing only adolescents. Hence in this paper the focus is towards adolescents' heart attack risk detection and classification. This is achieved by proposing a novel architecture which detects chances of heart attack in early stages using soft set theory and fuzzy rules. The performance of the proposed architecture is found to be good with respect to several parameters like accuracy, delay and efficiency.

关键词： Cardiac arrest Support vector machines Heart Computer architecture classification algorithms Electrocardiography

来源：评论

学校读者我要写书评

暂无评论

Simultaneous feature selection and feature weighting with K selection for KNN classification using BBO algorithm

Simultaneous feature selection and feature weighting with K ...

引用

Conference on Information and Knowledge Technology

作者： Ahmad A. Kardan Atena Kavian Amir Esmaeili Department of Computer Engineering and Information Technology Amirkabir University of Technology Tehran Iran

K nearest neighbor algorithm (K-NN) is considered as one of the machine learning algorithms for data classification. This algorithm suffers of some disadvantages such as sensitivity to the distance function, K value selection and high computational complexity (time and spatial). In this paper, a novel hybrid approach is proposed for simultaneous feature selection and feature weighting with k value selection of K-NN rule based on Biogeography based optimization (BBO). The 6 evolutionary algorithms and 14 non-evolutionary algorithms are used to compare and evaluate with the novel proposed algorithm (BBO-KNN). The experimental results signify that the BBO-KNN has higher efficiency compared to other methods and is led to higher classification rate as well as effective data dimension reduction.

关键词： classification algorithms Accuracy Algorithm design and analysis Machine learning algorithms Biological cells Sensitivity Data models

来源：评论

学校读者我要写书评

暂无评论

classification of pseudo-random sequences based on the random forest algorithm

Classification of pseudo-random sequences based on the rando...

引用

Ivannikov Memorial Workshop (IVMEM)

作者： Alexander V. Kozachok Andrey A. Spirin Alexander I. Kozachok Alexey N. Tsibulia Academy of the Federal Guard Service of the Russian Federationm Orel Russian Federation

The following topics are dealt with: cryptography; formal specification; formal verification; grid computing; data analysis; Java; storage management; watermarking; cryptographic protocols; and protocols.

ISBN: (数字)9781728190884

ISBN: (纸本)9781728190891

关键词： Protocols Statistical analysis Conferences Data compression classification algorithms Encryption Random forests

来源：评论

学校读者我要写书评

暂无评论

Associative classification over Data Streams

Associative Classification over Data Streams

引用

International Conference on Information Engineering and Computer Science (ICIECS)

作者： Zhen-Hui Song Yi Li Department of Computer ShiJiaZhuang Vocational Technology Institute Shijiazhuang China

Based on association rules, Associative classification (AC) has shown great promise over many other classification techniques on static dataset. However, the increasing prominence of data streams arising in a wide range of advanced application has posed a new challenge for it. This paper describes and evaluates AC-DS, a new associative classification algorithm for data streams which is based on the estimation mechanism of the Lossy Counting (LC) and landmark window model. We apply AC-DS to mining several datasets obtained from the UCI Machine Learning Repository and the result show that the algorithm is effective and efficient.

关键词： classification algorithms Itemsets Association rules Algorithm design and analysis Machine learning algorithms Accuracy

来源：评论

学校读者我要写书评

暂无评论

Driver's cognitive state classification toward brain computer interface via using a generalized and supervised technology

Driver's cognitive state classification toward brain compute...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Chun-Hsiang Chuang Pei-Chen Lai Li-Wei Ko Bor-Chen Kuo Chin-Teng Lin Institute of Electrical Control Engineering and Brain Research Center National Chiao Tung University Hsinchu Taiwan Graduate Institute of Educational Measurement and Statistics National Taichung University Taichung Taiwan Department of Biological Science and Technology and Brain Research Center National Chiao Tung University Hsinchu Taiwan

Growing numbers of traffic accidents had become a serious social safety problem in recent years. The main factor of the high fatalities was the obvious decline of the driver's cognitive state in their perception, recognition and vehicle control abilities while being sleepy. The key to avoid the terrible consequents is to build a detecting system for ongoing assessment of driver's cognitive state. A quickly growing research, brain-computer interface (BCI), offers a solution offering great assistance to those who require alternative communicatory and control mechanisms. In this study, we propose an alertness/drowsiness classification system based on investigating electroencephalographic (EEG) brain dynamics in lane-keeping driving experiments in a virtual reality (VR) driving environment with a motion platform. The core of the classification system is composed of dimension reduction technique and classifier learning algorithm. In order to find the suitable method for better describing the data structure, we explore the performances using different feature extraction and feature selection methods with different classifiers. Experiment results show that the accuracy is over 80% in most combinations and even near 90% under Principal Component Analysis (PCA) and Nonparametric Weighted Feature Extraction (NWFE) going with Gaussian Maximum Likelihood classifier (ML) and k-Nearest-Neighbor classifier (kNN), respectively. In addition, this developed classification system can also solve the individual brain dynamic differences caused from different subjects and overcome the subject dependent limitation. The optimized solution with better accuracy performance out of all combinations can be considered to implement in the kernel brain-computer interface.

关键词： Feature extraction Driver circuits Electroencephalography classification algorithms Brain modeling Principal component analysis Support vector machines

来源：评论

学校读者我要写书评

暂无评论

An Empirical Study of Sentiment Analysis on Movie Review using Machine Learning based classification Approach

An Empirical Study of Sentiment Analysis on Movie Review usi...

引用

International Conference on Information Systems and Computer Networks (ISCON)

作者： Vikram Rajpoot Ruchi Agrawal Ankur Chaturvedi Kunal Goyal GLA University Mathura

ISBN: (纸本)9781665447874

Sentiment analysis is the investigation of feelings and conclusions from any type of text. It is additionally named as assessment. This is extremely helpful to communicate the assessment of the gathering person. The strategy is utilized to discover the estimation of the individual as for a given wellspring of substance. The web-based platform consists of gigantic measure information as tweets, websites. In this paper, we have presented the sentiment analysis approaches on Movie review dataset using different procedures like Naïve Bayes, K-Nearest Neighbour and Random Forest.

关键词： Sentiment analysis Machine learning algorithms Films Estimation Motion pictures Computer networks classification algorithms

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 << < 476 477 478 479 480 481 482 483 484 485 > >>

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：