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

13,153 篇 会议
188 册 图书
160 篇 期刊文献

馆藏范围

13,500 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

9,042 篇 工学
- 7,532 篇 计算机科学与技术...
- 4,276 篇 软件工程
- 1,627 篇 信息与通信工程
- 1,525 篇 电气工程
- 1,246 篇 控制科学与工程
- 962 篇 生物工程
- 528 篇 机械工程
- 498 篇 生物医学工程（可授...
- 477 篇 动力工程及工程热...
- 470 篇 电子科学与技术（可...
- 323 篇 光学工程
- 310 篇 交通运输工程
- 296 篇 安全科学与工程
- 264 篇 材料科学与工程（可...
- 263 篇 化学工程与技术
3,509 篇 理学
- 2,195 篇 数学
- 1,058 篇 生物学
- 602 篇 物理学
- 582 篇 统计学（可授理学、...
- 473 篇 系统科学
- 244 篇 化学
1,864 篇 管理学
- 1,294 篇 管理科学与工程(可...
- 682 篇 图书情报与档案管...
- 541 篇 工商管理
594 篇 医学
- 496 篇 临床医学
- 405 篇 基础医学(可授医学...
- 223 篇 药学(可授医学、理...
303 篇 教育学
- 293 篇 教育学
251 篇 法学
- 228 篇 社会学
221 篇 经济学
- 219 篇 应用经济学
136 篇 农学
37 篇 军事学
21 篇 文学
6 篇 艺术学

主题

1,272 篇 optimization
1,083 篇 machine learning
1,021 篇 deep learning
463 篇 accuracy
454 篇 reinforcement le...
312 篇 computational mo...
303 篇 machine learning...
288 篇 training
273 篇 support vector m...
264 篇 feature extracti...
259 篇 predictive model...
244 篇 neural networks
223 篇 real-time system...
216 篇 genetic algorith...
207 篇 adversarial mach...
161 篇 particle swarm o...
155 篇 learning algorit...
151 篇 convolutional ne...
138 篇 internet of thin...
130 篇 data mining

机构

46 篇 chitkara centre ...
36 篇 chitkara univers...
30 篇 chitkara univers...
29 篇 the islamic univ...
18 篇 centre of resear...
18 篇 al-farahidi univ...
17 篇 lloyd institute ...
17 篇 department of co...
15 篇 school of comput...
14 篇 school of comput...
14 篇 gla university d...
14 篇 department of co...
13 篇 vishwakarma inst...
12 篇 college of manag...
11 篇 chitkara univers...
11 篇 school of comput...
10 篇 columbia univers...
10 篇 univ chinese aca...
10 篇 lovely professio...
10 篇 university of ch...

作者

13 篇 lima jose
13 篇 pereira ana i.
11 篇 wang wei
9 篇 rakesh kumar
9 篇 wang hui
9 篇 de-shuang huang
9 篇 ye jieping
8 篇 yang tianbao
8 篇 neeraj varshney
8 篇 r. santhana kris...
7 篇 zhang tao
7 篇 zhang lei
7 篇 li li
7 篇 buzdalov maxim
7 篇 wang jian
7 篇 huang heng
7 篇 hu rong
7 篇 yang yang
7 篇 todorov venelin
7 篇 zivkovic miodrag

语言

12,576 篇 英文
896 篇 其他
73 篇 中文
1 篇 阿拉伯文
1 篇 西班牙文
1 篇 俄文
1 篇 土耳其文

检索条件"任意字段=4th International Conference on Optimization Learning Algorithms and Applications"

共 13501 条记录，以下是4991-5000 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：

Continuous Self-adaptation of Control Policies in Automatic Cloud Management 27th

Continuous Self-adaptation of Control Policies in Automatic ...

引用

27th international European conference on Parallel and Distributed Computing (Euro-Par)

作者： Funika, Wlodzimierz Koperek, Pawel Kitowski, Jacek AGH Univ Sci & Technol Fac Comp Sci Elect & Telecommun Inst Comp Sci Al Mickiewicza 30 PL-30059 Krakow Poland AGH Univ Sci & Technol ACC Cyfronet AGH Ul Nawojki 11 PL-30950 Krakow Poland

ISBN: (纸本)9783031061561;9783031061554

Deep Reinforcement learning has been recently a very active field of research. the policies generated with use of that class of training algorithms are flexible and thus have many practical applications. In this paper we present the results of our attempt to use the recent advancements in Reinforcement learning to automate the management of resources in a compute cloud environment. We describe a new approach to self-adaptation of autonomous management, which uses a digital clone of the managed infrastructure to continuously update the control policy. We present the architecture of our system and discuss the results of evaluation which includes autonomous management of a sample application deployed to Amazon Web Services cloud. We also provide the details of training of the management policy using the Proximal Policy optimization algorithm. Finally, we discuss the feasibility to extend the presented approach to further scenarios.

关键词： Computing clouds Autonomous control Digital twin Deep Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Sequence-Graph Fusion Neural Network for User Mobile App Behavior Prediction

Sequence-Graph Fusion Neural Network for User Mobile App Beh...

引用

5th international Workshop on learning with Imbalanced Domains - theory and applications / European conference on Machine learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)

作者： Wang, Yizhuo Jiang, Renhe Liu, Hangchen Yin, Du Song, Xuan Southern Univ Sci & Technol Shenzhen Peoples R China Univ Tokyo Tokyo Japan

ISBN: (纸本)9783031434266;9783031434273

In recent years, mobile applications (apps) on smartphones have shown explosive growth. Massive and diversified apps greatly affect user experience. As a result, user mobile app behavior prediction has become increasingly important. Existed algorithms based on deep learning mainly conduct sequence modeling on the app usage historical records, which are insufficient in capturing the similarity between users and apps, and ignore the semantic associations in app usage. Although some works have tried to model from the perspective of graph structure recently, the two types of modeling methods have not been combined, and whether they are complementary has not been explored. therefore, we propose an SGFNN model based on sequence combined graph modeling, which is already publicly available as the Github repository https://***/ZAY113/SGFNN. Sequence Block, BipGraph Block, and HyperGraph Block are used to capture the user mobile app behavior short-term pattern, the similarity between users and apps, and the semantic relations of hyperedge "user-time-location-app", respectively. Two real-world datasets are selected in our experiments. When the app sequence length is 4, the prediction accuracy of Top1, Top5, and Top10 reaches 36.08%, 68.39%, 79.02% and 51.55%, 87.57%, 95.62%, respectively. the experimental results show that the two modeling methods can be combined to improve prediction accuracy, and the information extracted from them is complementary.

关键词： User app behavior prediction Deep learning Graph neural networks Hypergraph embedding

来源：评论

学校读者我要写书评

暂无评论

AI-Augmented Skill Development Roadmaps: Tailoring 12-Month learning Paths for Future-Ready Careers in Education 4.0 and Industry 4.0

AI-Augmented Skill Development Roadmaps: Tailoring 12-Month ...

引用

international conference on System Modeling & Advancement in Research Trends (SMART)

作者： Rahul Vadisetty Anand Polamarasetti Electrical Engineering Wayne State University Detroit MI USA Computer Science Andhra University Visakhapatnam AP India

ISBN: (数字)9798350380583

ISBN: (纸本)9798350380590

In fact, rapid convergence between Education 4.0 and Industry 4.0 demands adaptive learning models that would equip people with future-ready skills in the dynamically changing workforce. this work introduces AI-augmented skill development roadmaps, underlining how to design and implement personalized 12-month learning paths. the proposed framework is based on data-driven learner profiling, machine learning algorithms, and continuous adaptive assessments for optimization of building individual learning pathways toward emerging technology trends alignment. this review will be predicated on existing AI applications in competency development, identifying gaps in conventional models. It also involves the holistic roadmap structure: milestones, phases, and progression metrics. Case studies of real-world examples would then be delivered where AI-powered learning pathways have resulted in targeted competency development, employability, and lifelong learning. the key performance indicators will be defined to provide the effectiveness of the framework for scalability and adaptability. the findings bring to the fore that AI can cause a paradigm shift in skill gaps through enabling personalized learning at scale and furthering strategic goals related to Industry 4.0. this research makes a substantial contribution to the development of scalable education models for essential competencies that are part of the fast-evolving facets of digitalization.

关键词： Adaptation models Machine learning algorithms Engineering profession Reviews Scalability Key performance indicator Market research Fourth Industrial Revolution Artificial intelligence optimization

来源：评论

学校读者我要写书评

暂无评论

4th international conference on Advanced Network Technologies and Intelligent Computing, ANTIC 2024

4th International Conference on Advanced Network Technologie...

引用

4th international conference on Advanced Network Technologies and Intelligent Computing, ANTIC 2024

ISBN: (纸本)9783031837920

the proceedings contain 109 papers. the special focus in this conference is on Advanced Network Technologies and Intelligent Computing. the topics include: Exploratory Study on Different Transformer Models;visionLingua: Empowering Multimodal Understanding with Cutting-Edge Language Models;human Action Recognition Using Mediapipe Holistic Keypoints: A Deep learning Approach;machine learning for Waste-to-Energy: optimization and Predictive Analytics;enhanced Traffic Forecasting for Urban Planning Using DeepWalk Embeddings and Spatio-Temporal Graph Ordinary Differential Equation Model;fault Detection in Semiconductor Manufacturing Using Advanced Machine learning Techniques with Interpretability;fine-Tuning RetinaNet for Few-Shot Fruit Detection;Smart Street: AI-Powered Traffic Flow Enhancement with Adaptive Signal Control;a Hybrid Machine learning Approach for Accurate Milk Quality Classification;Designing VoiceGPT Chatterbox Concierge: A Personal AI Assistant for Daily Services Using Supervised Machine learning Based Speech Recognition Techniques;improved Classification Techniques Using Convolutional Neural Networks for Rice Plant Disease Detection;Enhancing Customer Segmentation and Behavior Prediction through Machine learning and Medium Gaussian SVM;Grapevine SDLC Model for Real-Time Fake News Classification;Detecting AI-Generated Text Using Fine-Tuned Transformers: A Study on Academic Integrity;MoReco: AI Model Recommendation and optimization for B5G Networks;file Prefetching Accuracy Enhancement Using Deep learning Approaches;Mamba Based Conditional GAN for Optical Cloud Removal of Satellite Images;a Hybrid Quantum Machine learning Model for Multi-class Classifier;adaptive Resource Management in Massive Machine-Type Communications Using Reinforcement learning;Advanced Machine learning and Features Based Data Analytics of Electricity Consumption in USA and India;cross-Domain Adversarial Attacks and Robust Defense Mechanisms for Multimodal Neural Networks;deep Featu

关键词：

来源：评论

学校读者我要写书评

暂无评论

Task Offloading and Resource Allocation Strategies Based on Proximal Policy optimization

Task Offloading and Resource Allocation Strategies Based on ...

引用

Natural Language Processing (ICNLP), international conference on

作者： Kai Liu Wujun Yang Dept. School of Communication and Information Engineering Xi’an University of Posts and Telecommunication Xi’an China

ISBN: (数字)9798350349115

ISBN: (纸本)9798350349122

In order to meet the service demands of new network applications and scenarios, computational offloading techniques in MEC have become a popular research issue. Aiming at solving the problems of delay deterioration and server resource scarcity caused by multi-users offloading tasks on edge servers at the same time, this paper firstly constructs a multi- terminal and single-server offloading model for tasks based on the queuing theory. Considering the user's delay experience under the delay-sensitive condition, introduces the weighted sum of the waiting probability and the task completion time as the optimization objective. On this basis, a proximal policy optimization-based computational offloading and resource allocation strategy is proposed. Finally, the simulation findings indicate that the algorithm proposed in this paper exhibits superior performance in optimizing the delay experience of user when compared to alternative algorithms.

关键词： Computational modeling Bandwidth Deep reinforcement learning Natural language processing Delays Servers Resource management optimization Queueing analysis

来源：评论

学校读者我要写书评

暂无评论

Electroencephalogram Data Analysed through the Lens of Machine learning to Detect Signs of Epilepsy 4

Electroencephalogram Data Analysed Through the Lens of Machi...

引用

4th international conference on Inventive Research in Computing applications, ICIRCA 2022

作者： Rajalakshmi, J. Ranjani, S.Siva Sugitha, G. Prabanand, S.C. Sethu Institute of Technology Research Scholar Department of Computer Science and Engineering Kariyapatti India Muthayammal Engineering College Department of Computer Science and Engineering Rasipuram India Bannari Amman Institute of Technology Department of Artificial Intelligence and Data Science Sathyamangalam India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

As most epileptic seizures only happen infrequently the EEG is essential for the categorization and diagnosis of epilepsy. Empirical interpretation of a first EEG has a low sensitivity (between 29 and 55% [29-55 percent]) when applied to adult patients. During EEG epochs in which seizures are not present, valuable EEG data is buried among the signals and is thus inaccessible to any clinician who does not have specialized training in EEG analysis. In order to distinguish people with generalized epilepsy from the general population, we create a multi-variate technique employing EEG data to comprehend the functional connectivity of the brain at the sensor level. the temporal, periodic, and time-frequency domains were probed using five different measurements to investigate eight distinct connection properties. the K-Nearest Neighbor method was used to evaluate the solution, and the results were compared to two groups: the first consisted of patients with epilepsy, and the second consisted of patients who had nonepileptic episodes. Both EG and HC groups demonstrated high levels of classification accuracy (89%), although EG showed significant spatial-temporal abnormalities in the front central regions at the beta frequency band compared to HC. Classification accuracy for EG and NEAD was only approximately 79% because of the well-documented comorbidity of NEAD and epileptic episodes. this study suggests that seizure-free EEG data may be used to reliably differentiate between those with HC and those with specialized epilepsy. Although more research is needed to develop a diagnostic tool that might aid in treatment. © 2022 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Fire Detection System using Deep learning Techniques 4

Fire Detection System using Deep Learning Techniques

引用

4th international conference on Inventive Research in Computing applications, ICIRCA 2022

作者： Srividhya, S. Sindhu, S. Sornalakshmi, K. Hemavathi, D. Rajaram, V. School of Computing Srm Institute of Science and Technology Data Science and Business Systems Chennai India School of Computing Srm Institute of Science and Technology Department of Networking and Communications Chennai India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

An image-based fire detection system is designed using an image dataset to train the model, and further, any image capturing device will be used for later prediction purposes. the training and prediction are done using deep learning techniques. Convolution Neural Network is used for implementation. As another fire identification innovation, picture fire location has as of late assumed a pivotal part in diminishing property misfortune and harm during a fire by disturbing clients at a beginning phase through early fire discovery. Picture fire location depends on an algorithmic investigation of pictures. Nonetheless, there is a lower precision, postponed recognition, and much calculation in like manner identification calculations, including physically and machine naturally separating picture highlights. the model is designed to alert the user via SMS and email along with a captured image of fire when a fire occurs. the proposed system in development aims at providing a detection system that can alert a user instantly at the time of a hazardous fire. the aim is to create an accurate model that does not result in false alerts. the model is trained using accurate image datasets to differentiate between a fire and a non-fire scenario. Existing models used the RGB-HIS colour space for their model. Particularly, it is used to obtain pre-detected areas rather than the traditional motion differential method. the centroid variety of candidates is used to measure the flame colour dispersions in subsequent frames. Multi-expert systems have the following;dispersion of colour and centroid movement are entrenched to classify fire based on testing various clips acquired by a surveillance camera in private confinement. © 2022 IEEE.

关键词： Fires

来源：评论

学校读者我要写书评

暂无评论

Innovations in Education: A Deep Dive into the Application of Artificial Intelligence in Higher learning

Innovations in Education: A Deep Dive into the Application o...

引用

Advance Computing and Innovative Technologies in Engineering (ICACITE), international conference on

作者： Anjar Sri Ciptorukmi Nugraheni Salim Widono Kundharu Saddhono Sri Yamtinah Farida Nurhasanah Tri Murwaningsih Universitas Sebelas Maret

ISBN: (数字)9798350360165

ISBN: (纸本)9798350360172

the landscape of education is fast-changing, fueled by technological developments that are promising to tear down traditional methodologies of learning. Among these promising to be transformational forces with huge potential in improving higher learning experiences is Artificial Intelligence (AI). this research paper discusses the innovative applications of artificial intelligence within the higher education field, synthesized for its multifaceted impact on the teaching-learning process and administration. this means that at the heart of the effects of AI in higher education is the power to facilitate tailor-made education conducted in line with individual needs and requirements. these AI-based platforms use cutting-edge algorithms and data analytics. they analyze performance data of students and clearly indicate areas where they could have strengths, weaknesses, or improvement. Educators can then be able to derive insights from this that would help in making the tailoring of content and strategies for instruction with maximal learning outcomes and have students engaged in mastering the material from a higher level. Such AI-driven adaptive learning systems offer students dynamic and interactive study experiences where content delivery is adapted in real-time based on student progression and levels of understanding. the adaptive approach caters to the variance in paces of learning while it enables students to be in control of their learning journey through self-directed attitudes towards learning and critical thinking.

关键词： Surveys Heart Ethics Technological innovation Data privacy Data analysis Education

来源：评论

学校读者我要写书评

暂无评论

Enhancing Robotics Online 3D Bin Packing: A Comparative Study of Conventional Heuristic and Deep Reinforcement learning Approaches

Enhancing Robotics Online 3D Bin Packing: A Comparative Stud...

引用

IEEE international conference on Automation Science and Engineering (CASE)

作者： Heng Xiong Kai Ding Wan Ding Xuchong Qiu Klaus Janschek Jianfeng Xu State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China BOSCH Corporate Research Technische Universität Dresden Germany

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Robotic object packing holds a wide array of practical applications across logistics and manufacturing sectors. the online 3D Bin Packing Problem (BPP) is a challenging task that involves online packing of three-dimensional boxes into a container while considering constraints and objectives. Unlike the offline version, where all boxes are known in advance, the online variant requires decisions about how to pack each box as it arrives, without prior knowledge of upcoming *** maximize space utilization, our study explores two distinct strategies: conventional heuristics-based algorithms and a deep reinforcement learning (DRL)-based approach. For the heuristic strategy, we propose four heuristic criteria alongside two variants of multi-objective optimization (MOO) algorithms. Quantitative experiments reveal that MOO outperforms single-objective approaches for online bin packing. In our DRL-based approach, we introduce a framework that leverages a candidate map that indicates the potentially feasible placements, ensuring a balanced exploration and exploitation in the considerable discrete action space. Experiments demonstrate the superior performance of our DRL-based approach compared to both DRL-based baseline methods and conventional approaches. Additionally, we discuss the limitations of DRL-based methods and offer practical recommendations for real-world applications.

关键词： three-dimensional displays Computer aided software engineering Heuristic algorithms Containers Deep reinforcement learning Explosions Manufacturing Robots optimization Logistics

来源：评论

学校读者我要写书评

暂无评论

Advancing Fake Profile Detection: A Machine learning Perspective

Advancing Fake Profile Detection: A Machine Learning Perspec...

引用

Intelligent Technologies (CONIT), international conference on

作者： Bharti Goyal Nasib Singh Gill Preeti Gulia Department of Computer Science & Applications Maharshi Dayanand University Rohtak India

ISBN: (数字)9798350349900

ISBN: (纸本)9798350349917

the development of Internet has made individuals’ lives simpler and more convenient in many ways. People from different parts of the world communicate with one another through a variety of social media platforms that are accessible online. Users of these platforms contribute data in order to share significant moments and recollections from their lives. the quantity of data stored on these sites continues to increase, which brings with it a rise in the potential threats to users’ privacy. there have been several attempts by cybercriminal actors to hack into these websites and steal sensitive information. In order to accomplish this mission, attackers create duplicate user accounts, known as fake profiles. these fake profiles harm society by spreading fake news, rumors, stealing user personal information, defaming celebrities, asking for money for funds etc. So, identification of fake profiles is the most pressing need of society, in terms of the protection of private data. this paper discusses various machine learning algorithms used in fake profile detection by different researchers, and a comparison of these techniques with their results has been made for aiming at identifying fake profiles. In order to accomplish this task, two Instagram dataset, Dataset1 Instagram fake and real accounts dataset ***, and Datase2 Instagram fake spammer genuine accounts dataset *** are used. the results obtained by both the datasets are compared using fifteen algorithms. the findings demonstrate that the result vary for same algorithm on different datasets. Voted Perceptron leads on dataset1, while SMO leads on dataset 2 in terms of Precision, Recall, F1-Score and Accuracy. these findings encourage us to conduct additional research in the related field.

关键词： Support vector machines Machine learning algorithms Social networking (online) Machine learning Pressing Web sites Multimedia communication

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 << < 491 492 493 494 495 496 497 498 499 500 > >>

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：