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

3,050 篇 会议
244 册 图书
127 篇 期刊文献

馆藏范围

3,416 篇 电子文献
5 种 纸本馆藏

日期分布

学科分类号

933 篇 工学
- 716 篇 计算机科学与技术...
- 526 篇 软件工程
- 221 篇 信息与通信工程
- 193 篇 控制科学与工程
- 165 篇 电气工程
- 88 篇 电子科学与技术（可...
- 71 篇 机械工程
- 67 篇 生物工程
- 61 篇 生物医学工程（可授...
- 57 篇 网络空间安全
- 53 篇 动力工程及工程热...
- 50 篇 化学工程与技术
- 45 篇 仪器科学与技术
- 39 篇 光学工程
- 35 篇 交通运输工程
- 30 篇 环境科学与工程（可...
- 27 篇 安全科学与工程
440 篇 理学
- 259 篇 数学
- 110 篇 物理学
- 83 篇 生物学
- 81 篇 统计学（可授理学、...
- 63 篇 化学
- 56 篇 系统科学
297 篇 管理学
- 193 篇 管理科学与工程(可...
- 134 篇 图书情报与档案管...
- 106 篇 工商管理
53 篇 医学
- 47 篇 基础医学(可授医学...
- 47 篇 临床医学
- 28 篇 药学(可授医学、理...
39 篇 经济学
- 39 篇 应用经济学
31 篇 法学
21 篇 教育学
18 篇 农学
3 篇 文学
3 篇 军事学

主题

43 篇 artificial intel...
31 篇 computational in...
22 篇 machine learning
22 篇 congresses.
18 篇 cloud computing
18 篇 distributed comp...
16 篇 software enginee...
16 篇 computer communi...
14 篇 real-time system...
14 篇 forecasting
13 篇 big data
13 篇 computational mo...
12 篇 internet of thin...
12 篇 computer science
12 篇 information syst...
12 篇 computer systems...
12 篇 data mining
12 篇 professional com...
11 篇 neural networks
11 篇 genetic algorith...

机构

11 篇 fukuoka institut...
9 篇 university of sa...
8 篇 florida internat...
8 篇 democritus unive...
8 篇 international in...
7 篇 infn sezione di ...
7 篇 università di pa...
7 篇 infn sezione di ...
7 篇 universidade de ...
7 篇 universität sieg...
7 篇 univ. grenoble a...
7 篇 universidad de m...
7 篇 universidade de ...
7 篇 università del s...
7 篇 torino
7 篇 palacky universi...
7 篇 gran sasso scien...
7 篇 palermo
7 篇 infn sezione di ...
7 篇 institute for as...

作者

14 篇 barolli leonard
12 篇 coleman a.
9 篇 anon
8 篇 flaggs b.
7 篇 giammarchi m.
7 篇 bismark k.
7 篇 fazzini n.
7 篇 avila g.
7 篇 emam m.
7 篇 de mitri i.
7 篇 covault c.e.
7 篇 deligny o.
7 篇 almeida cheminan...
7 篇 aglietta m.
7 篇 condorelli a.
7 篇 anastasi g.a.
7 篇 cataldi g.
7 篇 gaudu c.
7 篇 cobos cerutti a....
7 篇 brack j.

语言

3,272 篇 英文
76 篇 中文
74 篇 其他
3 篇 葡萄牙文
3 篇 俄文
1 篇 德文

检索条件"任意字段=Proceedings of the 7th International Conference on Algorithms, Computing and Systems"

共 3421 条记录，以下是3291-3300 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：

Ant Colony Optimization and Swarm Intelligence 2008

引用

丛书名： Lecture Notes in Computer Science

2008年

作者： Marco Dorigo Mauro Birattari Christian Blum Maurice Clerc thomas Stützle Alan Winfield

ISBN: (数字)9783540875277

ISBN: (纸本)9783540875260

this book constitutes the refereed proceedings of the 6th international Workshop on Ant Colony Optimization and Swarm Intelligence, ANTS 2008, held in Brussels, Belgium, in September 2008. the 17 revised full papers, 24 revised short papers, and 10 extended abstracts presented were carefully reviewed and selected from 91 submissions. the papers cover theoretical and foundational aspects of computational intelligence and related disciplines with special focus on swarm intelligence and are devoted to behavioral models of social insects and new algorithmic approaches, empirical and theoretical research in swarm intelligence, applications such as ant colony optimization or particle swarm optimization, and theoretical and experimental research in swarm robotics systems.

关键词： Ant algorithms Congresses. Mathematical optimization Computer programs Congresses.

来源：评论

学校读者我要写书评

暂无评论

Exploring Machine Learning to Predict Brain Tumour Disease

Exploring Machine Learning to Predict Brain Tumour Disease

引用

international conference on Contemporary computing and Informatics (IC3I)

作者： Sukrati Sharma Sunaina Basu Dev Shivahare Kirti Singh Prabhishek Singh Vimal Bibhu Just Dial Bangalore Karnataka India Department of Mathematics Amity University Greater Noida Uttar Pradesh India School of computer science & Engineering Galgotias University Greater Noida Uttar Pradesh India School of computing science & Engineering Bennett University Greater Noida Uttar Pradesh India School of Engineering & Technology Noida International University Greater Noida Uttar Pradesh India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

the demand of AI is increasing day by day in the medical field. Machine Learning (ML) is subset of AI. ML has become popular tool and widely used to detect several medical diseases at higher accuracy. Promising accuracy of ML algorithms depend on training of digital images like CT, MRI, X-rays etc. In this paper, CNN model is proposed to classify brain tumour into malignant and non-malignant class and comparative study using diverse ML algorithm is conducted and their accuracy is compared. this paper explores role of ML in clinical diagnosis, accurate prediction and clinical analysis regarding brain tumour disease based on various brain tumour dataset like figshare, brats, Kaggle. Proposed CNN model has achieved 98 % promising accuracy.

关键词： Accuracy Machine learning algorithms Magnetic resonance imaging Computed tomography Machine learning Brain modeling Clinical diagnosis Medical diagnostic imaging Tumors Cancer

来源：评论

学校读者我要写书评

暂无评论

Convolutional Neural Network Based Deep Neural Network Model for Electrocardiogram Records Classification 7

Convolutional Neural Network Based Deep Neural Network Model...

引用

7th international conference on Future Networks and Distributed systems, ICFNDS 2023

作者： Khudhur, Ahmed Mahmood Alwan, Mohammed Hasan Al Omairi, Qayssar Mahmood, Omar Abdulkareem Hammadi, Yousif I Muthanna, Mohammed Saleh Ali Aziz, Ahmed Muthanna, Ammar Information Technology Department College Of Computer Science And Information Technology Kirkuk University Iraq Department Of Communications Engineering College Of Engineering University Of Diyala Baqubah32001 Iraq Department Of Computer Engineering College Of Engineering University Of Diyala Iraq Bilad Alrafidain University College Diyala32001 Iraq Institute Of Computer Technologies And Information Security Southern Federal University Taganrog344006 Russia Department Of Computer Science Faculty Of Computer And Artificial Intelligence Benha University Egypt Department Of International Business Management Tashkent State University Of Economics Tashkent Uzbekistan Department Of Telecommunication Networks And Data Transmission The Bonch Bruevich Saint Petersburg State University Of Telecommunications Russia Department Of Applied Probability And Informatics Peoples Friendship University Of Russia Russia

ISBN: (纸本)9798400709036

Cardiovascular diseases, also known as CVDs, currently rank as the primary incidence of mortality. the present approach for identifying illnesses involves the analysis of the Electrocardiogram (ECG), an electronic diagnostic device utilized to capture the rhythm of the heart. Regrettably, the process of seeking out specialists to conduct analysis on a substantial volume of electrocardiogram (ECG) data results in a significant depletion of medical capabilities. Hence, the utilization of deep learning algorithms for the identification of ECG characteristics has progressively gained prominence. Nevertheless, there exist certain limitations associated with these conventional approaches, which necessitate the need for manual characteristic identification, intricate models, and extensive training duration. this study presents a novel and effective approach for categorizing the five different types of heartbeats in the MIT-BIH Arrhythmia database. the proposed method involves the utilization of a 16-layer deep one-dimensional convolutional neural network, which exhibits both robustness and efficiency in its classification performance. thus, the designed model is consisting of five-groups, first to fourth groups are the main feature extraction and mapping blocks, while the fifth group is fully connected and classification layers. the findings indicate that the model presented in this study has superior performance in terms of accuracy, precision, and F1-score. the proper classification of medical cases has a significant impact on the conservation of medical resources, hence positively influencing clinical practice. Additionally, the model training phase is characterized by its efficiency, since it does not significantly deplete resources. © 2023 ACM.

关键词： Electrocardiograms

来源：评论

学校读者我要写书评

暂无评论

Parameterized characterization for rotating-bending fatigue strength of high-strength metal components

Parameterized characterization for rotating-bending fatigue ...

引用

international conference on Airworthiness ＆ Fatigue-7th ICSAELS Series conference

作者： J.F.Zhang X.D.Bian D.Mu Key Laboratory for Mechanics in Fluid and Solid Coupling Systems Institute of MechanicsChinese Academy of Sciences

Most of the fatigue failure of components in aero-structures occurs on its surface or in subsurface *** order to promote the fatigue strength of material or component,more and more attention is paid on surface treatment *** better evaluating the quality of the surface,optimizing the surface process technique and selecting the process parameters,a quantitative characterization method and a relating mathematical model are *** studying the influence of the parameters of the surface modification layer on the fatigue properties of metal components,a parameterized characterization method for rotating-bending fatigue strength of high-strength metal component is proposed and a quantitative mathematical model is *** validation of the model is verified in terms of rotating-bending fatigue testing for M50NiL *** model can be used not only to evaluate the fatigue strength of metal components but also to provide some reference on surface treatment.

关键词： fatigue surface modification layer parameterized characterization evaluating model

来源：评论

学校读者我要写书评

暂无评论

the influence of surface roughness characteristics on fatigue stress concentration

The influence of surface roughness characteristics on fatigu...

引用

international conference on Airworthiness ＆ Fatigue-7th ICSAELS Series conference

作者： J.F.Zhang Q.Li D.Mu X.D.Bian Key Laboratory for Mechanics in Fluid and Solid Coupling Systems Institute of MechanicsChinese Academy of Sciences

Numerical simulations have been performed to analyze the influence of surface roughness on the fatigue stress concentration with finite element method（FEM）.the parameters to characterize the rough surface topology are analyzed,and the inherent relationships between the characteristic parameters of the rough surfaces are described based on statistical *** quantitative mathematical expressions for stress concentrations are given in terms of the dimensionless parameters of rough surface for both plane stress and plane strain states,and the consistent form is *** errors for the stress concentration factor（K） and the fatigue stress concentration factor（K_f） predicted from the proposed model were within 4%and 1%of those from FEM numerical *** show that the standard deviation of the valley radius of the surface profile must be taken into account as an important parameter in the prediction of fatigue stress concentration.

关键词： fatigue surface roughness characteristic parameter finite element simulation

来源：评论

学校读者我要写书评

暂无评论

Cognitive computing in E-Commerce Enhancing Supply Chain Management

Cognitive Computing in E-Commerce Enhancing Supply Chain Man...

引用

international conference on Contemporary computing and Informatics (IC3I)

作者： Mohammed Al Awadh K K Karthick K K Ramachandran Department of Industrial Engineering King Khalid University Abha Saudi Arabia Department of Management Science Saveetha Engineering College Thandalam Chennai India Management/Commerce/International Business Dr G R D College of Science Coimbatore Tamil Nadu India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

Cognitive computing has been posturing itself as the disruptive innovation that advances the supply chain management in e-commerce. this research aims at identifying how cognitive computing system can be incorporated in the supply chain in various areas including demand forecast, inventory replenishment, and customer relations. through the use of analytical capabilities, artificial intelligence (machine learning), and natural language processing, cognitive computing improves decision-making accuracy, eradicates redundancies, and dynamics timely improvements based on market trends. the study illustrates that cognitive computing not only leads to an enhanced structure of e-commerce supply chains but are also more responsive and flexible, thus leading to effective customer satisfaction and company advantage.

关键词： Analytical models Technological innovation Supply chain management Biological system modeling Computational modeling Supply chains Transportation Companies Electronic commerce Cognitive systems

来源：评论

学校读者我要写书评

暂无评论

Heart Disease Prediction Algorithm Based on Ensemble Learning

Heart Disease Prediction Algorithm Based on Ensemble Learnin...

引用

international conference on Dependable systems and their Applications (DSA)

作者： Ke Yuan Longwei Yang Yabing Huang Zheng Li School of Computer and Information Engineering Henan University International Joint Research Laboratory for Cooperative Vehicular Networks of Henan School of Computer and Information Engineering Henan University

ISBN: (数字)9780738124223

ISBN: (纸本)9781665419536

Nowadays, heart disease is one of the important causes of human deaths. According to statistics, deaths caused by heart disease account for about one-third of all deaths in the world. With further research, the use of machine learning to predict heart disease has become an essential method to prevent and treat heart disease. In recent years, machine learning based on big data analysis has been widely used in various software applications, but it has not been used on a large scale in disease prediction. In this article, we propose a new algorithm named hybrid gradient boosting decision tree with logistic regression (HGBDTLR) based on ensemble learning to improve the accuracy of machine learning in heart disease prediction. the actual results prove that the prediction accuracy of HGBDTLR algorithm can reach 91.8% in the Cleveland heart disease data set.

关键词： Heart Training Machine learning algorithms Software algorithms Big Data Prediction algorithms Diseases

来源：评论

学校读者我要写书评

暂无评论

State Space Design Cycle and Hardware in the Loop Testing and Verification 60

State Space Design Cycle and Hardware in the Loop Testing an...

引用

60th IEEE international Midwest Symposium on Circuits and systems (MWSCAS)

作者： Rahnamai, Kourosh Rowlands, Justin Western New England Univ Dept Elect & Comp Engn Springfield MA 01119 USA

ISBN: (纸本)9781509063895

Advances in real-time hardware in the loop (HIL) boards and software has provided an excellent opportunity to implement and test control algorithms rapidly on real systems [1-7]. Hardware in the loop development allows for rapid development, testing and verification of control systems. this paper, using a servo system as an example, clearly explores modern control systems design cycle, which includes real-time verification of the controller. this methodology illustrates design cycle from system specification, system constraints to controller design, HIL testing and verification of the developed controller. this rapid prototyping strategy to develop and test controllers can be used in industry as well as academia. In an academic environment, it helps student relate, better understand and implement theoretical concepts on real systems. Experiments described in this paper use a real-time hardware in the loop platform, which consists of a DC-servo control system, MATLAB, Simulink, dSPACE real-time hardware and ControlDesk software. this paper shows how this type of platform can is be used to verify system models and test designed state space controllers.

关键词： Control system analysis and design Hardware in the loop math model verification Rapid prototyping of controllers

来源：评论

学校读者我要写书评

暂无评论

From monoscale to multiscale modeling of fatigue crack growth:stress and energy density factor

From monoscale to multiscale modeling of fatigue crack growt...

引用

international conference on Airworthiness ＆ Fatigue-7th ICSAELS Series conference

作者： G.C.Sih International Center for Sustainability Accountability and Eco-Affordability of the Large and Small(ICSAELS)Lehigh University Key Laboratory of Pressure Systems and Safety Ministry of EducationSchool of Mechanical EngineeringEast China University of Science and Technology

the formalism of the earlier fatigue crack growth models is retained to account for multiscaling of the fatigue process that involves the creation of macrocracks from the accumulation of micro *** effects of at least two scales,say micro to macro,must be accounted *** same data can thus be reinterpreted by the invariancy of the transitional stress intensity factors such that the microcracking and macrocracking data would lie on a straight *** threshold associated with the sigrnoidal curve *** segmentation is shown to be a necessity for addressing multiscale energy dissipative processes such as fatigue and *** independency and energy release rate are monoscale criteria that can lead to unphysical results,violating the first *** ofmonoscale failure or fracture criteria to nanomaterials is taking toll at the expense of manufacturing super strength and light materials and structural components. this brief view is offered in the spirit of much needed additional research for the reinforcement of materials by creating nanoscale interfaces with sustainable time in *** step by step consideraton at the different scales may offer a better understanding of the test data and their limitations with reference to space and time.

关键词： multiscale fatigue monoscale dualscale stress intensity energy density macro micro nano spatial-temporal crack stability sustaibale time

来源：评论

学校读者我要写书评

暂无评论

Research on Multi-Channel Vision Platform for Intelligent Robots Based on Deep Learning

Research on Multi-Channel Vision Platform for Intelligent Ro...

引用

international conference on Information systems and Computer Aided Education (ICISCAE)

作者： Jinkun Hong Aquinas International Academy Ontario CA USA

ISBN: (数字)9798350350760

ISBN: (纸本)9798350350777

Load forecasting plays an indispensable role in ensuring the stability and economy of power supply. this study aims to deeply analyze the application of soft computing technology and data mining theory in the field of power system load forecasting. By introducing neural networks, especially Kohonen network and BP neural network, this study successfully realizes the robust clustering of load curves, the construction of feature curves, and the identification of abnormal curve patterns. Meanwhile, this paper combines the composite neural network and feature curves to effectively recognize and correct the abnormal data. In the field of fuzzy modeling, this study optimizes the structure of the fuzzy inference system using the CART algorithm and establishes a multi-parameter load forecasting model. Case studies confirm the effectiveness of these methods and highlight the strong potential of soft computing and data mining in improving load forecasting accuracy and data quality.

关键词： Accuracy Load forecasting Computational modeling Neural networks Predictive models Power system stability Power system reliability Data mining Forecasting Load modeling

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343页 << < 326 327 328 329 330 331 332 333 334 335 > >>

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：