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

11,382 篇 会议
102 篇 期刊文献
44 册 图书

馆藏范围

11,528 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

7,863 篇 工学
- 6,395 篇 计算机科学与技术...
- 3,774 篇 软件工程
- 1,491 篇 控制科学与工程
- 1,373 篇 电气工程
- 1,233 篇 信息与通信工程
- 873 篇 生物工程
- 556 篇 机械工程
- 428 篇 动力工程及工程热...
- 417 篇 生物医学工程（可授...
- 380 篇 交通运输工程
- 360 篇 电子科学与技术（可...
- 268 篇 光学工程
- 257 篇 安全科学与工程
- 234 篇 材料科学与工程（可...
- 222 篇 化学工程与技术
2,871 篇 理学
- 1,787 篇 数学
- 930 篇 生物学
- 484 篇 物理学
- 449 篇 统计学（可授理学、...
- 321 篇 系统科学
- 199 篇 化学
1,735 篇 管理学
- 1,285 篇 管理科学与工程(可...
- 582 篇 工商管理
- 535 篇 图书情报与档案管...
496 篇 医学
- 367 篇 临床医学
- 344 篇 基础医学(可授医学...
- 184 篇 药学(可授医学、理...
352 篇 教育学
- 342 篇 教育学
209 篇 法学
- 191 篇 社会学
204 篇 经济学
- 204 篇 应用经济学
112 篇 农学
28 篇 军事学
23 篇 文学
7 篇 艺术学

主题

964 篇 deep learning
866 篇 optimization
762 篇 machine learning
535 篇 accuracy
401 篇 reinforcement le...
275 篇 computational mo...
274 篇 training
271 篇 feature extracti...
261 篇 predictive model...
219 篇 real-time system...
203 篇 neural networks
202 篇 support vector m...
178 篇 particle swarm o...
150 篇 genetic algorith...
148 篇 convolutional ne...
147 篇 adversarial mach...
142 篇 machine learning...
139 篇 learning systems
134 篇 data models
132 篇 analytical model...

机构

56 篇 chitkara univers...
31 篇 chitkara centre ...
22 篇 chitkara univers...
19 篇 university of ch...
14 篇 university of sc...
14 篇 misr int univ fa...
14 篇 school of comput...
13 篇 univ chinese aca...
13 篇 institutes for r...
12 篇 centre of resear...
12 篇 al-farahidi univ...
12 篇 lviv polytech na...
11 篇 guangdong provin...
11 篇 lovely professio...
11 篇 lovely professio...
11 篇 school of comput...
11 篇 the islamic univ...
11 篇 national energy ...
11 篇 king mongkuts un...
10 篇 wuhan university...

作者

15 篇 wang tao
13 篇 liu yang
13 篇 yang yang
13 篇 wang wei
13 篇 wang hao
13 篇 liu wei
11 篇 zhang jie
10 篇 zhang tao
10 篇 lima jose
10 篇 li hao
9 篇 wang lei
9 篇 hassanien aboul ...
8 篇 shiva mehta
8 篇 zhang lei
8 篇 aleven vincent
8 篇 liu jun
8 篇 singh jagendra
8 篇 pereira ana i.
8 篇 nojima yusuke
8 篇 fotiadis dimitri...

语言

11,094 篇 英文
409 篇 其他
44 篇 中文
1 篇 西班牙文
1 篇 法文
1 篇 俄文
1 篇 土耳其文

检索条件"任意字段=4th Conference on Learning and Intelligent Optimization"

共 11528 条记录，以下是131-140 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：

Deep Reinforcement learning-Driven Path optimization in Multi-UAV Edge Computing Systems 4th

Deep Reinforcement Learning-Driven Path Optimization in Mult...

引用

4th International conference on Advanced Network Technologies and intelligent Computing-ANTIC-Annual

作者： Adhikari, Pronab Kumar Tomar, Abhinav Netaji Subhas Univ Technol Dept Comp Sci & Engn New Delhi India

ISBN: (纸本)9783031837821;9783031837838

Aerial drones, in general known as Unmanned Aerial Vehicles (UAVs), holds a longstanding history of being utilized within mobile networks as network processors;however, a shift has been observed where they are now being utilized as mobile servers within the framework of Mobile Edge Computing (MEC). this evolution is primarily attributed to their inherent flexibility, portability, robust line-of-sight communication capabilities, and cost-effectiveness, which allows for adaptable usage scenarios, thereby contributing to an increase in their utilization within both research and commercial settings. the essential characteristics of aerial drones have made them increasingly popular across a wide spectrum of civilian services, such as transportation, industrial monitoring, agriculture, forest fire management, and wireless services. Within the scope of this project, the focus lies on exploring MEC networks utilizing Unmanned Aerial Vehicles, where these UAVs undertake computational tasks provided by mobile terminal users (TUs). In order to guarantee the Quality-of-Service (QoS) for each TU, the UAV makes real-time modifications to its flight path by taking into consideration the positions of the mobile TUs, with the ultimate goal of improving the overall performance of the network and enhancing the user experience.

关键词： UAV Mobile Edge Computing Quality-of-service

来源：评论

学校读者我要写书评

暂无评论

Active Prewarning Technology for Smart Grid Based on Unsupervised learning 4

Active Prewarning Technology for Smart Grid Based on Unsuper...

引用

4th International conference on Machine learning and intelligent Systems Engineering (MLISE)

作者： Qu, Ruiting Tian, Xiaolei Chen, Shuo State Grid Liaoning Informat & Commun Co Shenyang Peoples R China

ISBN: (纸本)9798350375084;9798350375077

this paper proposes an early warning technology for power grid cloud platform microservice architecture alarm information based on unsupervised learning, discovers potential abnormal patterns and rules, sends out early warning signals in a timely manner, and improves the ability to identify and process power grid cloud platform microservice architecture alarms. According to the above steps, based on the establishment of the power grid business microservice operation alarm log alarm information knowledge base, this article will study the cloud platform operation monitoring data scoring algorithm, classify the cloud platform monitoring information, and then filter out the suspected abnormal data. For different business types of complex scenarios, research on abnormal information classification mining technology based on statistical models, proximity, clustering and classification, apply improved K-means clustering[1] and LOF outlier detection technology[2] to establish a combined detection model, and detect anomalies the data is clustered and outliers detected to achieve active early warning technology of unsupervised learning.

关键词： smart grid unsupervised learning K-means clustering LOF

来源：评论

学校读者我要写书评

暂无评论

intelligent Manufacturing Systems Problem with AGV transportation consideration based on Hybrid Imperialist Competitive Algorithm 4

Intelligent Manufacturing Systems Problem with AGV transport...

引用

4th International conference on Computer Communication and Artificial Intelligence (CCAI)

作者： Dong, Yuan Rui, Zhou Li, Xiaohui Zhao, Yi ChangAn Univ Sch Elect & Control Engn Xian Peoples R China

ISBN: (纸本)9798350362770;9798350362763

this paper delves into the problem of scheduling manufacturing workshop operations with multiple Automated Guided Vehicles (AGVs), aiming to minimize the maximum completion time. To tackle this issue, a novel approach based on the Imperialist Competitive Algorithm is proposed with the integration of a disjunctive graph-based critical path method and a variable neighborhood descent method. Furthermore, the variable neighborhood descent. this enhances the algorithm's optimization capability prevents it from getting trapped in local optimal. through comprehensive experiments on the test datasets, the effectiveness and stability of the proposed algorithm are validated.

关键词： intelligent Manufacturing Systems Imperialist Competitive Algorithm Neighborhood Structure Critical Path

来源：评论

学校读者我要写书评

暂无评论

Research on efficient deep learning method based on blockchain consensus mechanism 4

Research on efficient deep learning method based on blockcha...

引用

4th International conference on Computer Communication and Artificial Intelligence (CCAI)

作者： Wang, Shuangming Zhang, Tuo Shaanxi Tech Coll Finance & Econ Sch Big Data & Artificial Intelligence Xianyang Peoples R China

ISBN: (纸本)9798350362770;9798350362763

Aiming at the problem of trustworthy model aggregation for distributed deep learning in blockchain platforms, this paper proposes a deep learning algorithm based on the efficient consensus mechanism of blockchain. the algorithm improves the efficiency of model aggregation by improving the Byzantine fault-tolerant consensus algorithm based on the voting mechanism and uses the Krum algorithm based on differential privacy to improve the convergence of model aggregation. through experiments, it is shown that the communication complexity is reduced from O(2n(2)) to O(n(2)), and the aggregation model is still able to converge and maintain a high classification accuracy with 30% malicious nodes

关键词： blockchain deep learning consensus algorithm krum algorithm

来源：评论

学校读者我要写书评

暂无评论

Prediction of Hazardous Asteroids Using Machine learning 4

Prediction of Hazardous Asteroids Using Machine Learning

引用

4th International conference on Emerging Systems and intelligent Computing, ESIC 2024

作者： Surekha, Nemmaluri Purna Nanjundan, Preethi Bashir, Shahid Christ University Pune Department of Data Science Lavasa India

ISBN: (纸本)9798350349856

As the need for early detection and mitigation of potential threats from near-Earth objects continues to grow, this study presents a comprehensive approach to predicting hazardous asteroids through the application of machine learning techniques. With the increasing interest in safeguarding our planet from potential impact events, the accurate classification and prediction of hazardous asteroids is of paramount importance. this research leverages a diverse dataset comprising a wide array of asteroid characteristics, including orbital parameters, physical properties, and historical impact data, to train and validate machine learning models. the study employs a combination of feature engineering, data preprocessing, and state-of-the-art machine learning algorithms to assess the risk posed by asteroids in near-Earth space. © 2024 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Developing a Deep learning Based Grab Cut Target Image Automatic Segmentation Algorithm 4

Developing a Deep Learning Based Grab Cut Target Image Autom...

引用

4th International conference on Machine learning and intelligent Systems Engineering (MLISE)

作者： Liang, Jianfeng Palaoag, thelma D. Univ Cordilleras Dept Comp Sci Baguio Philippines Univ Beibu Gulf Coll Elect & Informat Engn Qinzhou City Peoples R China

ISBN: (纸本)9798350375084;9798350375077

In response to the problem that traditional Grab Cut algorithms cannot achieve automatic segmentation of foreground targets, this paper proposes an automatic segmentation algorithm that combines deep learning and graph cutting. Firstly, the YOLOv4 model is trained on a common dataset to achieve automatic recognition of multiple targets, and the coordinate parameters of the automatic recognition box are converted into vertex coordinate parameters for automatic annotation. then, the Grab Cut algorithm is iterated to complete image segmentation. At the same time, in order to further improve the accuracy of image segmentation, the regression box loss function of the YOLOv4 model has been improved. the experimental results show that the automatic segmentation algorithm proposed in this paper has better segmentation performance than the traditional unsupervised MeanShift algorithm and is close to the Grab Cut algorithm. After improvement, the automatic segmentation algorithm has improved in both IoU and PA values.

关键词： Image segmentation Deep learning YOLOv4 Grab Cut

来源：评论

学校读者我要写书评

暂无评论

Research on Resource Scheduling Algorithm optimization in Cloud Computing Environment Based on Deep learning 4

Research on Resource Scheduling Algorithm Optimization in Cl...

引用

4th International conference on Electronic Information Engineering and Computer Communication, EIECC 2024

作者： Wang, Chuanchen Guo, Ruifeng Xiu, Pengfei Li, Xuerao Wang, Hongliang Chinese Academy of Sciences Shenyang Institute of Computing Technology Shenyang China

ISBN: (纸本)9798331534622

With the rapid advancement of cloud computing technology, user demands for Quality of Service (QoS) are continuously increasing. As a crucial link between user requirements and resource provisioning, resource scheduling has become a key focus in algorithm optimization research. Deep learning, a core technique in artificial intelligence, has been widely adopted to improve the efficiency of resource allocation in cloud computing, enabling intelligent and dynamic solutions. this paper provides a comprehensive review of deep learning-based resource scheduling algorithms, analyzing current progress and identifying existing challenges. It begins by introducing the fundamental concepts of resource scheduling and its pivotal role in maintaining service quality. Common deep learning models and their application scenarios in this domain are summarized. Next, recent research advances are discussed in detail, covering design principles, model training techniques, optimization strategies, and real-world outcomes. the strengths and limitations of various algorithms are compared, with a particular focus on metrics such as real-time responsiveness, accuracy, and computational complexity. Furthermore, this paper explores ongoing challenges, including data imbalance, limited generalization capabilities, constraints in real-time performance, and the need for energy efficiency. Finally, it envisions future research directions, emphasizing the potential of reinforcement learning and transfer learning to address these challenges. It is posited that continuous breakthroughs in deep learning will drive novel approaches for resource scheduling, advancing cloud computing services toward greater intelligence and efficiency. © 2024 IEEE.

关键词： Contrastive learning

来源：评论

学校读者我要写书评

暂无评论

Detection of Bone Fracture Using Deep learning 4

Detection of Bone Fracture Using Deep Learning

引用

4th International conference on Emerging Systems and intelligent Computing, ESIC 2024

作者： Pujitha, B. Raga Sravya, K. Krishnasai, N. Aparna, Ch V R Siddhartha Engineering College Department of Ece Vijayawada India

ISBN: (纸本)9798350349856

this research delves into the realm of bone fracture detection in medical X-ray images by harnessing the power of Deep learning, specifically employing the DenseNet and VGG19 Convolutional Neural Network (CNN) architectures. through extensive training and meticulous optimization, we navigate the intricacies of these models in the context of radiology, aiming to augment the precision and effectiveness of fracture identification. Our investigation unfolds against the backdrop of a comprehensive dataset comprising a diverse array of X-ray images, encompassing both normal and fractured bone instances. Rigorous experimentation and evaluation, utilizing a spectrum of performance measures encompassing accuracy, precision and recall reveal compelling results. Our CNN models exhibit a superior diagnostic prowess, surpassing conventional methodologies and demonstrating remarkable sensitivity and specificity in fracture detection. Beyond these empirical achievements, we explore the clinical implications of our findings, envisioning these models as indispensable tools that could empower radiologists to expedite accurate diagnoses, ultimately elevating the standard of patient care and alleviating the burdens on healthcare practitioners. In sum, this study sets the stage for transformative advancements within the field of analysis of medical images and computer-aided diagnosis, ushering in a new eraof fracture detection within the realm of radiological sciences. © 2024 IEEE.

关键词： Medical imaging

来源：评论

学校读者我要写书评

暂无评论

Data Enhancement Strategy Using Reinforcement learning and Xgboost with BlockChain Security 4

Data Enhancement Strategy Using Reinforcement Learning and X...

引用

4th International conference on intelligent Technologies, CONIT 2024

作者： Selvapriya, S. Manvizhi, N. Ajay, S. Kavya, V.K. Gilmary, Rosario Ifet College of Engineering Dept. of Information Technology Tamilnadu Villupuram India

ISBN: (纸本)9798350349900

the enormous volumes of data generated by Next Generation Sequencing (NGS) technology have transformed genomics and made efficient data analysis techniques necessary. To create data analytics applications, the extraction, transformation, and loading (ETL) process is necessary. In understanding data features, representation, storage, I/O operations, intermediate findings, in-memory analysis, and total processing time, the data format is crucial, as this study emphasizes. Data conformance is required for effective analysis since different machine learning and data mining algorithms require different types and forms of data. In this paper, we explore data format-centric optimization of the ETL process for NGS data analysis. We investigate how computing efficiency and analytical correctness are affected by the choice of data type. By using distributed computing and parallel processing, we evaluate the effectiveness of several data formats in NGS data analysis processes, such as FASTQ, BAM, and VCF. Our study offers suggestions for developing data analytics applications in the genomics field by clarifying the relationship between data format, ETL, and algorithmic needs. We also look at the trade-offs between resource usage and data format choice. In the end, our study contributes to more accurate and efficient genomics research by addressing the urgent need for well-informed data format options in NGS data analysis. © 2024 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Research on the Economic Benefits and Operational Strategy optimization of Photovoltaic- Energy Storage- Direct Current- Flexibility Building 4

Research on the Economic Benefits and Operational Strategy O...

引用

4th International conference on intelligent Power and Systems, ICIPS 2024

作者： Han, Dong Gu, Wen Jiang, Benjian Kong, Liang State Grid Shanghai Economic Research Institute Shanghai China Shanghai Lianyuan Intelligent Technology Co. Ltd Shanghai200235 China

ISBN: (纸本)9798331532765

the PEDF building model is crucial for advancing the global energy transition, reducing greenhouse gas emissions, and increasing economic benefits. However, due to its long-term advantages, users often overlook its immediate impacts, hindering widespread adoption. this paper presents three optimization strategies: AC/DC energy-saving, regulation response, and economic operation. A comprehensive evaluation system quantitatively compares these strategies. Simulations show that the regulation response strategy outperforms in stabilizing grid loads and mitigating fluctuations, while the energy-saving and economic strategies are less effective in grid stability. © 2024 IEEE.

关键词： Energy saving

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 << < 10 11 12 13 14 15 16 17 18 19 > >>

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：