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

135 篇 期刊文献
116 篇 会议

馆藏范围

251 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

211 篇 工学
- 117 篇 计算机科学与技术...
- 52 篇 电气工程
- 41 篇 信息与通信工程
- 30 篇 控制科学与工程
- 19 篇 软件工程
- 15 篇 机械工程
- 15 篇 石油与天然气工程
- 14 篇 材料科学与工程（可...
- 14 篇 环境科学与工程（可...
- 13 篇 网络空间安全
- 11 篇 仪器科学与技术
- 11 篇 电子科学与技术（可...
- 10 篇 动力工程及工程热...
- 9 篇 交通运输工程
- 8 篇 土木工程
- 7 篇 水利工程
- 5 篇 安全科学与工程
- 4 篇 建筑学
- 4 篇 测绘科学与技术
41 篇 理学
- 12 篇 生物学
- 11 篇 数学
- 10 篇 化学
- 5 篇 物理学
- 5 篇 地球物理学
- 3 篇 系统科学
41 篇 管理学
- 36 篇 管理科学与工程(可...
- 4 篇 公共管理
16 篇 医学
- 8 篇 基础医学(可授医学...
- 7 篇 临床医学
7 篇 教育学
- 6 篇 教育学
3 篇 农学
1 篇 哲学
1 篇 经济学
1 篇 法学

主题

251 篇 decision tree al...
27 篇 data mining
24 篇 machine learning
7 篇 random forest al...
6 篇 random forest
6 篇 classification
5 篇 support vector m...
5 篇 decision trees
5 篇 feature extracti...
5 篇 artificial intel...
5 篇 feature selectio...
4 篇 classification a...
4 篇 information gain
4 篇 cloud computing
4 篇 id3 algorithm
3 篇 naive bayes algo...
3 篇 fault diagnosis
3 篇 machine learning...
3 篇 statistical feat...
3 篇 phasor measureme...

机构

2 篇 shanghai inst te...
2 篇 thiagarajar coll...
2 篇 univ naples fede...
2 篇 gannan normal un...
2 篇 wayne state univ...
2 篇 feu inst technol...
2 篇 k ramakrishnan c...
2 篇 mahath amma inst...
2 篇 chendhuran coll ...
2 篇 nehru inst techn...
2 篇 tongji univ dept...
1 篇 xian int studies...
1 篇 nano manufacturi...
1 篇 sv coll engn ece...
1 篇 state grid jibei...
1 篇 univ sains islam...
1 篇 jianghan univers...
1 篇 woosong univ dep...
1 篇 kn toosi univ te...
1 篇 univ canberra fa...

作者

3 篇 taeseon yoon
3 篇 wu hao
3 篇 liu yunxiang
3 篇 sugumaran v.
2 篇 tamburis oscar
2 篇 zhang lei
2 篇 kumar hemantha
2 篇 lagman ace c.
2 篇 amarnath m.
2 篇 tang jing
2 篇 miao duoqian
2 篇 lin bowen
2 篇 ravichandran m.
2 篇 dan shao
2 篇 chen min
2 篇 kim kyoung-yun
2 篇 hemantha kumar
2 篇 ahmed fahim
2 篇 liu caihui
2 篇 fatone gerardo

语言

238 篇 英文
10 篇 其他
3 篇 中文

检索条件"主题词=decision tree algorithm"

共 251 条记录，以下是181-190 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：

Quadrotor-Enabled Autonomous Parking Occupancy Detection

Quadrotor-Enabled Autonomous Parking Occupancy Detection

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Wang, Yafeng Ren, Beibei Texas Tech Univ Dept Mech Engn Lubbock TX 79409 USA

ISBN: (纸本)9781728162126

Large special-events parking involves various parking scenarios, e.g., temporary parking and on-street parking. Their occupancy detection is challenging as it is unrealistic to construct gates/stations for temporary parking areas or build a sensor-based detection system to cover every single street. To address this issue, this study develops a quadrotor-enabled autonomous parking occupancy detection system. A camera-equipped quadrotor is flying over the parking lot first;then the images are captured by the on-board camera of the quadrotor and transferred to the ground station;finally, the ground station will process and release the occupancy information to the driver's mobile devices. The decision tree learning algorithm is adopted to determine the optimal flying speed for the quadrotor to balance the trade-off between the detection efficiency and accuracy. In order to tackle the complex environment in real-life parking, a convolutional neural network (CNN)-based vehicle detection model has been trained and implemented, where the realistic factors, e.g., passing pedestrians and tree blocking, are considered. Experiments are conducted to illustrate the effectiveness of the proposed system.

关键词： Parking occupancy detection quadrotor optimized flying speed decision tree algorithm convolutional neural network (CNN)

来源：评论

学校读者我要写书评

暂无评论

Machine learning based cardiovascular disease prediction

Machine learning based cardiovascular disease prediction

引用

International Conference on Advanced Materials for Innovation and Sustainability (ICAMIS)

作者： Chinnasamy, P. Kumar, S. Arun Navya, V. Priya, K. Lakshmi Boddu, Siva Sruthi MLR Inst Technol Dept Comp Sci & Engn Hyderabad India Bethesda Inst Technol & Sci Dept Comp Sci & Engn Gwalior India East Point Coll Engn & Technol Dept Elect & Commun Engn Bangalore India PERI Inst Technol Dept Elect & Commun Engn Chennai India MLR Inst Technol Dept Comp Sci & Engn Hyderabad India

In past few years, one of the really tough situations in medicine is already making predictions cardiac dysfunction. Almost any moment, roughly one patient dies through myocardial infarction with in present era. Due to the difficulty of forecasting cardiac sickness, it is vital to systematize the procedure in place to minimize the risk associated with and to educate the patient well enough in preparation. The risk of cardiovascular disease in the World is tremendous. The accurate and thorough assessment of a physician's cardiovascular risk is critical for reducing the incidence and severity attack and stroke and improving cardiovascular protection. In order to solve this issue, we are proposing method to discover these heart abnormalities as soon as reasonably practicable to avert fatal consequences. The next step is to determine whether or not the user is at risk of developing cardiovascular disease. It also answers difficult problems concerning heart detection of diseases, allowing clinicians to make better clinical decisions. Medical specialists have accumulated a large number of medical data that can be analysed and important fact retrieved. Machine learning approaches can improve in the prognosis and early identification of heart illness after hypothesis testing. Copyright (c) 2022 Elsevier Ltd. All rights *** and peer-review under responsibility of the scientific committee of the International Conference on Advanced Materials for Innovation and Sustainability.

关键词： Heart disease Machine learning K -nearest Classifier Ensemble classifier decision tree algorithm

来源：评论

学校读者我要写书评

暂无评论

Clustering-Based Network Intrusion Detection System 5

Clustering-Based Network Intrusion Detection System

引用

5th IEEE Conference on Dependable and Secure Computing (IEEE DSC)

作者： Fan, Chun-I Lai, Yen-Lin Shie, Cheng-Han Natl Sun Yat Sen Univ Dept Comp Sci & Engn Kaohsiung Taiwan

ISBN: (数字)9781665421416

ISBN: (纸本)9781665421416

The increasing sophistication of network attacks and the inability of traditional defensive techniques such as firewalls or weak passwords against them have led researchers to propose network intrusion detection systems. Many network intrusion detection systems using machine learning techniques have been proposed, but the detection performance of some systems can be further improved. In addition, many systems adopted multiple machine learning classifiers to cooperate in generating detection results, but the individual classifiers in the system are often difficult to operate independently, limiting the flexibility of the system. This paper presents a Clustering-Based Network Intrusion Detection System, which applies the concept of clustering to detect network attacks by using the K-Nearest Neighbor algorithm for the initial detection of network attack types, and the decision tree algorithm specializes in detecting specific types of attacks. This improves the detection performance of the system and maintains the usability of an individual classifier.

关键词： Intrusion Detection System Machine Learning Clustering K-Nearest Neighbor algorithm decision tree algorithm

来源：评论

学校读者我要写书评

暂无评论

Analytics on the Impact of Leadership Styles and Leadership Outcome 9th

Analytics on the Impact of Leadership Styles and Leadership ...

引用

9th Asian Conference on Intelligent Information and Database Systems (ACIIDS)

作者： Ahmad, Waseem Akhtaruzamman, Muhammad Waiariki Inst Technol Rotorua New Zealand

ISBN: (纸本)9783319544304

Data mining and machine learning approaches are helping organisations to streamline and optimise their processes and assisting management to devise more effective and efficient business strategies. In organisations, management or leadership style play an important role in employees motivation, work satisfaction, work commitment and productivity. Moreover, leadership style shapes up the organisational culture. The aim of this paper is to explore the impact of various leadership styles on employees using data mining techniques. A significant research has taken place in this area using simple statistical methods such as correlation and regression analysis. However, no research has been conducted in this area which used data mining algorithms to extract useful information from the data to examine how leadership styles influence/affect employees. In this research, rule and decision tree based algorithms are used to extract actionable information from the collected data.

关键词： Data mining Leadership styles Rule based algorithms decision tree algorithm Management

来源：评论

学校读者我要写书评

暂无评论

Recognition of Different Emergency Situation through Body Gesture Using Microsoft Kinect Sensor 11

Recognition of Different Emergency Situation through Body Ge...

引用

11th IEEE International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )

作者： Tolentino, Roselito E. Guinto, Pinky Mae F. Maypa, Dorothy Ysabelle B. De La Salle Univ Dasmarinas Coll Engn Architecture & Technol Dasmarinas Philippines

ISBN: (纸本)9781728130446

This study aim to recognize gestures that may serve as an indication for an emergency situation. Different gesture that indicates an emergency condition has been observe and studied that will be used as comparison and recognition for recognition. In this study emergency situation are classified into three category namely medical, life threating condition and disaster. The acquisition of gestures was done using the latest camera technology of today which is the MS Kinect sensor. The researchers used the skeletal tracking capability of the sensor to acquire data that will represent the movement or gesture of the person. The recognition of this gesture with respect to an actual medical emergency will be done using decision tree algorithm.

关键词： Emergency situation Gesture recognition decision tree algorithm Microsoft Kinect

来源：评论

学校读者我要写书评

暂无评论

A flow redirection decision mechanism using data mining on NEMO environments

A flow redirection decision mechanism using data mining on N...

引用

10th International Conference on Advanced Communication Technology

作者： Jung, Yukyong Kim, Mihui Chae, KiJoon Yoon, Jooyoung Jin, Jongsam Ewha Womans Univ Dept Comp Sci & Engn Seoul South Korea KT Infra Lab Mobile Internet Dev Dept Seoul South Korea

ISBN: (纸本)9788955191356

As constructing ubiquitous environment, the various researches for the integration of heterogeneous networks are now under way. Multihoming is one of important issues In these researches to provide effective mobility. In order to support high quality service and seamless connectivity, it is necessary to provide an efficient FR (Flow Redirection) for the integrated network. Especially, mobile router with multiple interfaces should decide FR based on network condition for the efficient use of resources. In this paper, we propose a FR decision mechanism on mobile network (NEMO) via combined data mining technologies with multiple attributes presenting network condition. We assume that the mobile router has WLAN and WiBro interface toward Internet. At first, In order to heuristically choose candidate attributes, we analyze the WLAN/WiBro specification documents [5][6] and the considered QoS parameters in these networks. Then, we apply various data obtaining from QualNet [12] In various cases to decision tree algorithm, in order to theoretically select the influential attributes in FIR decision. Finally, me acquire a FR decision model through the neural network with data for chosen attributes. Our simulation results show that our FR can provide the improved performances in comparison with current handover using only signal strength.

关键词： multihoming flow redirection decision algorithm decision tree algorithm neural network mobile network

来源：评论

学校读者我要写书评

暂无评论

Storage-Efficient tree Structure with Level-Ordered Unary Degree Sequence for Packet Classification 3

Storage-Efficient Tree Structure with Level-Ordered Unary De...

引用

3rd International Symposium on Computing and Networking (CANDAR)

作者： Kitamura, Yuta Iwata, Akira Mohri, Masami Shiraishi, Yoshiaki Nagoya Inst Technol Dept Sci & Engn Simulat Nagoya Aichi Japan Gifu Univ Informat & Multimedia Ctr Gifu Japan Kobe Univ Dept Elect & Elect Engn Kobe Hyogo Japan

ISBN: (纸本)9781467397971

Packet classification is an essential function in Internet routers that provides advanced network services such as virtual private networks (VPNs) and quality of service (QoS). decision tree-based packet classification algorithms such as HiCuts and HyperCuts allow the tradeoff between storage and throughput in the experimental result with the real life rulesets. However, the memory consumption of these algorithms remains high when high throughput is required. In this paper, we propose the tree data structure whose storage is small maintaining high throughput. It is based on the two ideas: The first is to use Level Ordered Unary Degree Sequence (LOUDS) which is a succinct representation of a tree structure. A general tree of n nodes is usually represented in pointer form, requiring 64n bits in 64-bit architecture, whereas LOUDS requires 2n+o(n) bits. Because LOUDS can access any child node from its parent one in constant time, the tree traversal is fast. The second is reducing the information contained in the tree node. This also reduces storage requirements without affecting search speed. The proposed data structure requires up to approximately one ninth less memory than pointer-formed tree, and the time complexity of a packet classification is equivalent to the pointer-formed tree.

关键词： packet classification decision tree algorithm succinct representation level-ordered unary degree sequence

来源：评论

学校读者我要写书评

暂无评论

Data Mining algorithms(KNN & DT) Based Predictive Analysis on Selected Candidates in Academic Performance 11

Data Mining Algorithms(KNN & DT) Based Predictive Analysis o...

引用

11th International Conference on Cloud Computing, Data Science and Engineering (Confluence)

作者： Ramalingam, M. Ilakkiya, R. Kongu Engn Coll Dept Informat Technol Erode Tamil Nadu India

ISBN: (纸本)9781665414517

we are presenting a predictive analysis of the academic performance of the students in Kongu Engineering College based on the academic performance of the passed out students. The performance of the students both in academic and in the placement is degrading every year which needs to be analyzed in order to improve the performance of the students for the upcoming batches. The placement performance of the students purely depends on academic performance and also on co-curricular performance. So, both will be taken for consideration. The involvement in the co-curricular activities and extra-curricular activities also affects the placement performance of the students. Thus, the data relating in the academic results, co-curricular activities, extracurricular involvement details and other personal details has to be considered for the prediction. The datasets are collected from various resources and the primary thirty six parameters were considered as parameters that have high impact on placement performance. The missing details were filled manually with the help of the faculties. Chi-square method is used for selecting the features that matches both the placed and non-placed students. Classification models were created to predict the placement performance of the students at the end of the last semester for each dataset.

关键词： Data Mining KNN decision tree algorithm Data Analytics

来源：评论

学校读者我要写书评

暂无评论

An Attributes Correlation Based Learning Guidance Model

An Attributes Correlation Based Learning Guidance Model

引用

4th International Multi-Conference on Society, Cybernetics and Informatics

作者： He, Binbin Fang, Zhiyi Sun, Bo Zhou, Lingxi Zhang, Yunchun Jilin Univ Coll Comp Sci & Technol Changchun 130012 Peoples R China

ISBN: (纸本)9781936338122

Using the theory of Web Data Mining, this paper proposes a physics discipline personalized learning evaluation system model based on decision tree algorithm. The overall structure of this system model, which is applied to the network-based education, is presented. The key part of the model, data collection module and personalized evaluation module are introduced. The advantages and disadvantages of the ID3 algorithm and the C4.5 algorithm are analyzed respectively. Taking the comparison of the two algorithms and the unique characteristics of the personalized learning system into consideration, a new_C4.5r decision tree rule simplification algorithm based on attributes correlation is proposed in this paper. The results from a set of experiments shows that the new_C4.5r decision tree algorithm outperforms the previous ones in running time, the size of the rule sets and overhead.

关键词： Web data mining personalized learning decision tree algorithm

来源：评论

学校读者我要写书评

暂无评论

Prediction of road traffic congestion based on random forest

Prediction of road traffic congestion based on random forest

引用

作者： Liu, Yunxiang Wu, Hao School of Computer Science and Information Engineering Shanghai Institute of Technology Shanghai China

ISBN: (纸本)9781538636749

With the process of urban modernization becoming faster and faster, there are more and more vehicles in the city, and the situation of urban traffic congestion is becoming more and more serious. In this paper, a model of traffic congestion prediction is constructed by using machine learning classification algorithm - random forest to construct traffic congestion state prediction model. The random forest algorithm has the characteristics of high robustness, high performance and high practicability. The weather conditions, time period, special conditions of road, road quality and holiday are used as model input variables to establish road traffic forecasting model. Finally, the results show that the traffic prediction model established by using the random forest classification algorithm has a prediction accuracy of 87.5%, and the generalization error is low, and it can be effectively predicted. Moreover, the calculation speed is fast, and it has stronger applicability to the prediction of congested condition. © 2017 IEEE.

关键词： decision tree algorithm Prediction accuracy Random forest Traffic congestion

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26页 << < 15 16 17 18 19 20 21 22 23 24 > >>

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：