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

8,424 篇 会议
50 篇 期刊文献
29 册 图书

馆藏范围

8,503 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4,426 篇 工学
- 3,376 篇 计算机科学与技术...
- 2,256 篇 软件工程
- 1,099 篇 信息与通信工程
- 818 篇 控制科学与工程
- 769 篇 电气工程
- 357 篇 生物工程
- 334 篇 电子科学与技术（可...
- 255 篇 机械工程
- 251 篇 动力工程及工程热...
- 195 篇 生物医学工程（可授...
- 185 篇 网络空间安全
- 178 篇 仪器科学与技术
- 148 篇 交通运输工程
- 140 篇 安全科学与工程
- 139 篇 光学工程
- 115 篇 化学工程与技术
2,204 篇 理学
- 1,653 篇 数学
- 392 篇 生物学
- 367 篇 统计学（可授理学、...
- 331 篇 物理学
- 305 篇 系统科学
- 118 篇 化学
1,107 篇 管理学
- 804 篇 管理科学与工程(可...
- 366 篇 图书情报与档案管...
- 335 篇 工商管理
174 篇 医学
- 151 篇 临床医学
- 145 篇 基础医学(可授医学...
146 篇 法学
- 121 篇 社会学
132 篇 文学
- 128 篇 新闻传播学
114 篇 经济学
- 112 篇 应用经济学
58 篇 教育学
43 篇 农学
16 篇 军事学
9 篇 艺术学

主题

1,132 篇 convergence
442 篇 cloud computing
411 篇 optimization
342 篇 computational mo...
293 篇 genetic algorith...
230 篇 information tech...
200 篇 algorithm design...
196 篇 particle swarm o...
195 篇 neural networks
182 篇 resource managem...
178 篇 servers
175 篇 training
170 篇 internet of thin...
162 篇 computer archite...
143 篇 mobile computing
142 篇 real-time system...
141 篇 wireless sensor ...
137 篇 educational inst...
136 篇 costs
129 篇 deep learning

机构

37 篇 university of ch...
28 篇 state key labora...
25 篇 college of compu...
25 篇 chitkara univers...
22 篇 amrita vishwa vi...
18 篇 beijing key labo...
17 篇 school of comput...
15 篇 university of sc...
15 篇 shenyang institu...
15 篇 college of compu...
15 篇 school of inform...
14 篇 school of comput...
14 篇 department of co...
14 篇 college of infor...
13 篇 faculty of infor...
13 篇 college of compu...
13 篇 national univers...
13 篇 institute of com...
12 篇 communication un...
12 篇 state key labora...

作者

40 篇 jeong jongpil
24 篇 kim dong-seong
20 篇 lee jae-min
19 篇 yang yang
14 篇 wang hui
14 篇 pan jeng-shyang
13 篇 wang lei
12 篇 zhiwei ye
12 篇 dong-seong kim
11 篇 sampedro gabriel...
11 篇 peeta basa pati
11 篇 younghan kim
11 篇 jongpil jeong
10 篇 jongwon kim
10 篇 rajagopal shinu ...
10 篇 lee jae min
9 篇 jie yang
9 篇 li li
9 篇 liu yang
9 篇 jae-min lee

语言

8,333 篇 英文
143 篇 其他
38 篇 中文
1 篇 法文

检索条件"任意字段=International Conference on Computing and Convergence Technology"

共 8503 条记录，以下是201-210 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：

Research on Photovoltaic Maximum Power Point Tracking technology Based on Combined Algorithms 2

Research on Photovoltaic Maximum Power Point Tracking Techno...

引用

2nd international conference on Signal Processing and Intelligent computing, SPIC 2024

作者： Shu, Tianluo Shi, Zhengang Shenyang Ligong University School of Information Science and Engineering Shenyang China

ISBN: (纸本)9798350368888

The photovoltaic array exhibits multiple peak power outputs under partial shading conditions. Traditional maximum power point tracking (MPPT) algorithms can get stuck at local maximum power points. To address this issue, a novel MPPT algorithm is proposed based on a combination of the Tuna Swarm Optimization (TSO) and the Particle Swarm Optimization (PSO) for photovoltaic systems. The algorithm achieves a complementary advantage of both methods, accelerating the convergence speed of the TSO in the later stages and avoiding the issue of the PSO easily falling into local optimal values. In the MATLAB/Simulink environment, a photovoltaic array simulation model is established. The simulation results indicate that the algorithm can quickly and accurately search for the global maximum power point. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

来源：评论

学校读者我要写书评

暂无评论

Hybrid Multi-objective Harris-Hawks and Moth-Flame Optimization Algorithm for Efficient Task Offloading strategy in IoT-Based Fog computing Applications

Hybrid Multi-objective Harris-Hawks and Moth-Flame Optimizat...

引用

2024 international conference on Knowledge Engineering and Communication Systems, ICKECS 2024

作者： Saranya, M. Pabitha, P. Department of Computer Science and Engineering Salem636308 India Anna University Department of Computer Technology MIT Campus Chennai Chromepet600044 India

ISBN: (纸本)9798350359688

In the domain of Internet of Things (IoT)-based fog computing, efficient task offloading strategies play a pivotal role in optimizing resource utilization and enhancing system performance. This work presents a novel approach, the Hybrid Multi-objective Harris-Hawks and Moth-Flame Optimization Algorithm (HMHMFOA), for addressing the task offloading optimization challenge in fog computing environments. The proposed approach combines the strengths of the Harris-Hawks Optimization (HHO) and Moth-Flame Optimization (MFO) algorithms to strike a balance between exploration and exploitation in the search space, resulting in faster convergence and higher-quality solutions. The hybridization method is precisely engineered to capitalize on the complementary characteristics of the two algorithms, resulting in improved optimization performance. Experimental evaluations of IoT-based fog computing scenarios show that the HMHMFOA outperforms baseline algorithms in terms of numerous optimization targets, such as latency minimization, energy efficiency, and resource usage. The results demonstrate the efficacy of the proposed approach in supporting efficient task offloading decision-making, hence contributing to the advancement of fog computing applications. This study paves the way for future research into hybrid optimization strategies geared to IoT-centric computing paradigms. © 2024 IEEE.

关键词： Fog computing

来源：评论

学校读者我要写书评

暂无评论

Simulation and Interactive Experience of Chinese Landscape Art with Combination of Virtual Reality technology 3

Simulation and Interactive Experience of Chinese Landscape A...

引用

3rd international conference on Intelligent computing, Communication and convergence, ICI3C 2023

作者： Xu, Pengpeng Shandong Huayu University of Technology School of Mechanical Engineering Dezhou China

ISBN: (纸本)9798350343922

In view of the problems existing in the simulation and interactive experience of Chinese garden art landscape, such as user experience, low accuracy of landscape simulation, insufficient landscape content and lack of individuality, this paper used Virtual Reality (VR) technology to study the simulation and interactive experience of Chinese garden art landscape. In this paper, Three-Dimensional (3D) modeling techniques were compared, and 3D Studio Max was selected for virtual garden simulation. It focused on the research of VR modeling technology and virtual system realization, as well as the activity experience brought by VR technology to landscape users, and the paper aim at improving the user's sense of experience. The error rate of the simulation method of garden art landscape based on VR technology was below 3.43%, and the average error rate of 20 experiments was 2.54%. The introduction of VR technology has brought a new way of viewing, which can be a panoramic rendering of the tour, but also can be a free roam within the model scene. © 2023 IEEE.

关键词： Virtual environments

来源：评论

学校读者我要写书评

暂无评论

Benign Non-Convex Optimization Techniques for Training Neuro-Inspired Architectures

Benign Non-Convex Optimization Techniques for Training Neuro...

引用

2024 OPJU international technology conference on Smart computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Roy, Vandana Kumar, S. Vinod Raj, Vijilius Helena Lakhanpal, Sorabh Yadav, Dinesh Kumar Alzuhairi, Rafil A. Gyan Ganga Institute of Engineering and Technology DoEC M.P. Jabalpur India Institute of Aeronautical Engineering Hyderabad Dundigal India New Horizon College of Engineering Department of Applied Sciences Bangalore India Lovely Professional University Phagwara India Lloyd Institute of Engineering & Technology Knowledge Park II Uttar Pradesh Greater Noida201306 India National University of Science and Technology College of Health and Medical Technology Dhi Qar64001 Iraq

ISBN: (纸本)9798350373783

In non-convex optimization contexts, neuronal network optimization is difficult yet crucial. The novel Adaptive Ensemble of Benign Non-Convex Optimization Algorithms (ABNOA) improves neuron-inspired structure training. SGD is trapped in local minima when there are non-convex loss surfaces;therefore, it doesn't always work. ABNOA solves these issues by dynamically selecting, combining, and fine-tuning optimization algorithms. This builds a versatile, dependable optimization mechanism. We tested ABNOA against typical speed evaluation methods using several metrics. Our analysis indicated that ABNOA performs better in several key areas. It lets you choose a method based on the optimization circumstances. This accelerates convergence. ABNOA's Adaptive Parameter Tuning (APT) fine-tunes hyperparameters in real time, improving algorithm efficiency and flexibility. Accelerating convergence improves training efficiency. It can manage complex loss landscapes, escape local minima, and finetune hyperparameters, giving it a full solution for non-convex neural network improvement for students and practitioners. According to the findings, ABNOA might transform complicated neural network training and advance AI. © 2024 IEEE.

关键词： Convex optimization

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Strategy Whale Optimization Algorithm for Edge computing Task Scheduling 11th

A Hybrid Strategy Whale Optimization Algorithm for Edge Comp...

引用

11th international conference on Signal and Information Processing, Network and Computers, ICSINC 2023

作者： Sun, Qizheng Yuan, Changqing Liu, Naijia Xu, Enqing Ma, Fei Li, Wei China Academy of Information and Communications Technology Beijing China

ISBN: (纸本)9789819721153

For the task scheduling problem in edge computing scenarios, whale optimization algorithm (WOA) can be used to solve this non-deterministic polynomial situation (NP-hard). However, WOA is prone to local extreme values and slow convergence speed. To address these issues, we developed an innovative algorithm incorporating adaptive weights, Levy flight strategies, and Gaussian variation to improve the whale optimization algorithm’s global search capacity and convergence speed, ultimately helping to reduce delays and energy consumption in edge computing task scheduling. We applied the new algorithm to solve edge computing task scheduling problems using Matlab, simulating varying numbers of edge nodes and tasks. Subsequently, we compared our algorithm with four benchmark algorithms, including the original whale algorithm and other improved versions. The results demonstrate that our algorithm outperforms others in relation to optimization delay, energy consumption, and overall efficacy, demonstrating its efficacy in addressing the edge computing task scheduling problem. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

Design of Big Data Scheduling Optimization Algorithm Based on Deep Reinforcement Learning

Design of Big Data Scheduling Optimization Algorithm Based o...

引用

2024 international conference on Telecommunications and Power Electronics, TELEPE 2024

作者： Chen, Xiao Guangdong Polytechnic of Science and Technology Guangdong Zhuhai519000 China

ISBN: (纸本)9798350369212

With the advent of the network era, data processing and optimization has become a key issue. Under this background, the research aims to study the big data scheduling optimization algorithm based on Deep Reinforcement Learning (DRL) to improve the efficiency and quality of data processing. In this article, an optimization algorithm of big data scheduling based on DRL is proposed. Through DRL technology, computers can schedule computing tasks and allocate resources independently according to historical data and real-time information, thus realizing more intelligent data processing. The research results show that the DRL-based big data scheduling optimization algorithm can significantly improve computing efficiency, reduce resource waste and optimize task scheduling when dealing with large-scale data. The big data scheduling optimization algorithm based on DRL has obvious advantages in running time, convergence and scheduling accuracy, and provides a more efficient and intelligent data processing method for practical application fields. © 2024 IEEE.

关键词： Data centers

来源：评论

学校读者我要写书评

暂无评论

Dynamic Load Balancing for Energy-Delay Tradeoff in a Cloud-RSU-Vehicle Architecture 14

Dynamic Load Balancing for Energy-Delay Tradeoff in a Cloud-...

引用

14th international conference on Information and Communication technology convergence, ICTC 2023

作者： Choi, Pyeongjun Yoon, Pildo Kwak, Jeongho Dgist Daegu Korea Republic of

ISBN: (纸本)9798350313277

Advanced autonomous driving services at Level 4 and above eliminate the need for constant driver supervision, enabling vehicles to respond autonomously to various driving scenarios. The integration of components under edge environment such as the On Board Unit (OBU), Road Side Units (RSUs), and cloud infrastructure, facilitated by V2X communication, enhances perception, decision-making, and control capabilities. However, existing standards lack guidance on efficient computing resource management in autonomous driving systems. To address this, we propose a dynamic computing load balancing algorithm for the cloud-RSU-vehicle architecture. This algorithm optimizes resource allocation and utilization, considering network conditions, computational capabilities, and processing queues using Lyapunov optimization techniques. The stability of the algorithm and trade-off between processing delay and energy consumption is inspected through simulation. © 2023 IEEE.

关键词： Edge computing Load balancing Lyapunov optimization

来源：评论

学校读者我要写书评

暂无评论

An Improved Image Defogging Algorithm Based on Dehazenet Network 2

An Improved Image Defogging Algorithm Based on Dehazenet Net...

引用

2nd international conference on Signal Processing and Intelligent computing, SPIC 2024

作者： Bai, Jingping Ren, Shiqing Fang, Zhao Shenyang Ligong University School of Information Science and Engineering Shenyang China Guangzhou College of Technology and Business Guangzhou China

ISBN: (纸本)9798350368888

The image dehaze technology is particularly important. This paper adopts the traditional physical model and deep learning network model approach, using the improved dehazenet network, using three different scales of convolution kernel for feature extraction of the original foggy image, and in the feature learning process using 3×3 tiny convolutional kernel to increase the model's depth;in order to avoid the network overfitting as well as to enhance the convergence speed of the network, the batch after convolution was added Batch Normalization processing is added after the convolution to estimate the transmittance t , and the original bootstrap filter is improved to a weighted bootstrap filter so as to better strengthen the edge information, and the quadtree method is used to estimate the atmospheric light value A instead of the original method to ensure a more accurate estimation of the atmospheric light. Using RESIDE dataset, the outdoor image with sky, the building image and the indoor restaurant image are used for the defogging experiments and the three values of PSRN, MSE and SSIM are evaluated. © 2024 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

A Microservice-based MLOps Platform for Efficient Development of AI Services in an Edge-Cloud Environment 14

A Microservice-based MLOps Platform for Efficient Developmen...

引用

14th international conference on Information and Communication technology convergence, ICTC 2023

作者： Kim, Chorwon Kim, Geon-Yong Kim, Sungchang Honam Research Center Gwangju Korea Republic of

ISBN: (纸本)9798350313277

With the advancement of Internet of Things (IoT) and Artificial Intelligence (AI) technologies, outcomes derived from diverse sets of collected data are finding applications in the business domain. In particular, edge AI technology, which combines edge computing and artificial intelligence, emerged to address real-time response limitations, is garnering considerable attention as a solution to the real-time response constraints faced by AI services within operated cloud environments. Nevertheless, the development of AI services within an edge-cloud environment presents numerous challenges, such as limited computing resources at the edge, the portability of learning models, and dependencies on code libraries during the build phase. Consequently, various open source projects and companies are actively advancing MLOps solutions. In this paper, we describe the development of a microservice-based MLOps platform utilizing open source for the development of AI services and the deployment of generated models in an edge-cloud environment built using lightweight edge hardware, software, and designated servers assuming the role of a cloud system. © 2023 IEEE.

关键词： Cloud computing Edge computing Kubeflow Kubernetes MLOps

来源：评论

学校读者我要写书评

暂无评论

Optimization of IRS-assisted OFDMA SWIPT Systems with Dynamic Subcarrier Allocation and AC computing 14

Optimization of IRS-assisted OFDMA SWIPT Systems with Dynami...

引用

14th international conference on Information and Communication technology convergence, ICTC 2023

作者： Vu, Binh-Minh Shin, Oh-Soon Soongsil University Department of Information Communication Convergence Technology Seoul Korea Republic of Soongsil University School of Electronic Engineering Seoul Korea Republic of

ISBN: (纸本)9798350313277

This study aims to explore the potential of an intelligent reflecting surface (IRS) in facilitating simultaneous wireless information and power transfer (SWIPT) in an orthogonal frequency division multiple access (OFDMA) system. A power-splitting (PS) protocol is employed to enable both energy harvesting (EH) and information decoding (ID). Moreover, an alternating current computing (ACC) is integrated into the EH receivers to directly utilize the harvested AC power, unlike the conventional direct current computing (DCC) approach. Specifically, we consider joint optimization of beamforming, dynamic subcarrier allocation (SA), IRS phase shift, PS coefficient, and ACC coefficient for the IRS-assisted OFDMA-SWIFT system, with the objective of maximizing the overall sum rate. To solve the optimization problem, we propose an alternating optimization (AO) framework combined with inner approximation (IA) methods. Numerical results demonstrate the effectiveness of the proposed system, as compared to alternative approaches. © 2023 IEEE.

关键词： alternating current computing (ACC) alternating optimization (AO) energy harvesting (EH) intelligent reflecting surface (IRS) subcarrier allocation (SA)

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 << < 17 18 19 20 21 22 23 24 25 26 > >>

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：