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

1,325 篇 会议
27 册 图书
7 篇 期刊文献

馆藏范围

1,359 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

973 篇 工学
- 918 篇 计算机科学与技术...
- 635 篇 软件工程
- 236 篇 信息与通信工程
- 131 篇 控制科学与工程
- 101 篇 生物工程
- 97 篇 电气工程
- 64 篇 安全科学与工程
- 60 篇 动力工程及工程热...
- 58 篇 交通运输工程
- 58 篇 网络空间安全
- 47 篇 机械工程
- 47 篇 生物医学工程（可授...
- 42 篇 仪器科学与技术
- 29 篇 建筑学
- 28 篇 环境科学与工程（可...
354 篇 理学
- 183 篇 数学
- 113 篇 生物学
- 74 篇 统计学（可授理学、...
- 58 篇 化学
- 41 篇 物理学
- 31 篇 系统科学
347 篇 管理学
- 237 篇 管理科学与工程(可...
- 213 篇 图书情报与档案管...
- 121 篇 工商管理
62 篇 法学
- 52 篇 社会学
61 篇 医学
- 54 篇 临床医学
- 50 篇 基础医学(可授医学...
- 32 篇 药学(可授医学、理...
47 篇 经济学
- 47 篇 应用经济学
28 篇 教育学
- 28 篇 教育学
14 篇 农学
7 篇 文学
2 篇 军事学

主题

256 篇 big data
79 篇 artificial intel...
67 篇 cloud computing
63 篇 machine learning
50 篇 computational mo...
49 篇 deep learning
42 篇 internet of thin...
41 篇 data models
35 篇 training
27 篇 data mining
25 篇 neural networks
24 篇 smart cities
23 篇 predictive model...
23 篇 edge computing
21 篇 computational in...
21 篇 feature extracti...
19 篇 industries
18 篇 object detection
17 篇 social networkin...
16 篇 data privacy

机构

14 篇 ajou univ dept a...
13 篇 school of big da...
12 篇 renmin univ chin...
11 篇 beijing key lab ...
9 篇 college of compu...
7 篇 university of ch...
7 篇 beijing universi...
6 篇 school of comput...
6 篇 key laboratory o...
6 篇 school of comput...
6 篇 key laboratory o...
6 篇 shandong fundame...
5 篇 college of big d...
5 篇 national enginee...
5 篇 shiga university...
5 篇 ajou univ dept i...
5 篇 riken center for...
5 篇 gaoling school o...
5 篇 chongqing univ s...
5 篇 college of intel...

作者

13 篇 shin hyunjung
10 篇 liu yong
7 篇 geng xin
6 篇 zhou xiaokang
6 篇 dai fei
6 篇 mariano vladimir...
6 篇 li shaojie
6 篇 wang jun
5 篇 xu ning
5 篇 wang xiaofei
5 篇 li xiuhua
5 篇 yang yang
5 篇 su bing
5 篇 kim myungjun
5 篇 zhao wei
5 篇 qi jinli
5 篇 wu yanmin
5 篇 jin hai
5 篇 gao yanxia
5 篇 liu yiwen

语言

1,331 篇 英文
21 篇 其他
9 篇 中文
1 篇 西班牙文

检索条件"任意字段=International Conference on Big Data Intelligence and Computing, DataCom 2022"

共 1359 条记录，以下是251-260 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：

IoT Device Identification Base on Inter-flow Correlation Analysis Using Graph Neural Network 9

IoT Device Identification Base on Inter-flow Correlation Ana...

引用

9th international conference on big data computing and Communications, bigCom 2023

作者： Peng, Chuang Tan, Xiaobin Xie, Peng Li, Mengxiang Wang, Hao Chen, Shuangwu University of Science and Technology of China Hefei China Hefei Comprehensive National Science Center Institute of Artificial Intelligence Hefei China

ISBN: (纸本)9798350331240

With the development of IoT, as one of the key technologies of IoT intelligence, IoT device identification is becoming increasingly important. However, the heterogeneity of devices and the sparsity of communication traffic data pose difficulties for IoT device identification. In this paper, we analyze the behavior and relationships between multiple flows of IoT traffic before concluding that there exist temporal correlations between multiple flows generated by one device. Based on this, an inter-flow temporal correlation graph (TCG) is constructed. A node in the TCG corresponds to a flow, and its features are the properties of the flow itself. An edge represents the temporal correlation between two flows. Then, taking into account the inter-flow temporal correlation, we propose a graph neural network-based IoT device identification method (TCG-DI). The effectiveness of TCG-DI is demonstrated through experiments based on open-source dataset and self-made dataset with high identification accuracy. © 2023 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Pheromone Matrix Eigenvalue-based Convergence Assessment Indicator for Ant Colony Optimization 11

Pheromone Matrix Eigenvalue-based Convergence Assessment Ind...

引用

11th international conference on Machine intelligence Theory and Applications, MiTA 2024

作者： Li, Xu Shi, Lin Li, Jian-Yu Xu, Jing Zhan, Zhi-Hui South China University of Technology School of Computer Science and Engineering Guangzhou510006 China Guangdong University of Finance and Economics Research Center of Intelligent Computing & Big Data Technology Guangdong Guangzhou510320 China Nankai University College of Artificial Intelligence Tianjin300350 China

ISBN: (纸本)9798350385670

As a crucial member of the evolutionary computation (EC), ant colony optimization (ACO) converges to the optimal result through a continuous process of iterative optimization. However, determining the convergence status of an ant colony remains a challenging task without well-established methods. To this end, this paper proposes a global evaluation indicator - average absolute eigenvalue of pheromone matrix (AAEPM) by constructing a pheromone matrix and analyzing its eigenvalue variations. This indicator aims to assess the convergence status of the ant colony during the evolutionary process. Experimental results show that the AAEPM is correlated with the convergence status of ACO and is not significantly influenced by algorithm parameters and problem scale. © 2024 IEEE.

关键词： Anthropogenic

来源：评论

学校读者我要写书评

暂无评论

Enhanced Sentiment Analysis of Medical Application using BERT and TextCNN 5

Enhanced Sentiment Analysis of Medical Application using BER...

引用

5th international conference on Machine Learning, big data and Business intelligence, MLBDBI 2023

作者： Shi, Wenyu Mariano, Vladimir Y. National University College of Computing and Information Technologies Manila Philippines Anhui Xinhua University School of Big Data and Artificial Intelligence Hefei Anhui230088 China

ISBN: (纸本)9798350359930

As Internet technology advances increasingly, the Internet penetration rate in every area of the world is gradually increasing, and there are more and more Internet users, and the e-commerce platform has also grown. In order to help doctors understand the patient's psychological state and supply better diagnosis and treatment., all major hospital and online medical platforms provide comment areas to display the comments made by patients with previous medical experience. By collecting and interpreting the text of published comments for sentiment analysis, users can get the real opinions of other users about doctors and hospitals, and doctors and hospitals can also see first-hand feedback from patients. However, with the accumulation of comment text, it is difficult for users to easily obtain effective information just because of massive text data, and the emotional tendency obtained by traditional analysis algorithms is relatively vague. Therefore, it is very important to quickly obtain the overall emotional orientation of the review text and accurately obtain the emotional orientation of all aspects in the review. A model integrating BERT and TextCNN is hereinto proposed to extract emotional features and analyze emotional information in the comments. The experiment results on comment dataset of medical application indicate that this approach performs well. © 2023 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Swarm intelligence Based data Selection Mechanism for Reputation Generation in Social Cloud

Swarm Intelligence Based Data Selection Mechanism for Reputa...

引用

2022 international conference on Machine Learning, big data, Cloud and Parallel computing, COM-IT-CON 2022

作者： Kumar, Santosh Goyal, Sandip Kumar Mullana Ambala India

ISBN: (数字)9781665496025

ISBN: (纸本)9781665496025

Cloud computing has evolved in every area of service generation and has also become an area of interest for researchers for the last couple of years. A social cloud is a cloud network that is connected by users who know each other in some manner. When service orientation takes place between the people who are known to each other, trust or reputation becomes a serious issue because if the user trusts the provider due to any connection, and if the provided service is not done in a significantly good manner, the user will be disappointed at the end the service level agreement gets violated. To solve this issue, researchers have shown interest in finding meta-heuristics-based Swarm intelligence based solutions and they are discussed in the article as well. This research article aims to find the best solution which fits into provider selection when it comes to providing the user the best experience. To do so, machine learning-based k-means is used and Artificial Bee Colony (ABC) is being enhanced. The proposed Enhanced ABC (E-ABC) algorithm is compared with state of art solutions in terms of successful and trustworthy communication. © 2022 IEEE.

关键词： Swarm intelligence

来源：评论

学校读者我要写书评

暂无评论

Task Scheduling Scheme for Mobile Edge computing via Bayesian Classifier 3

Task Scheduling Scheme for Mobile Edge Computing via Bayesia...

引用

3rd international conference on Computer, big data and Artificial intelligence, ICCBDAI 2022

作者： Wang, Yu Liu, Shixi School of Computer Science and Technology Anhui University Anhui Province Hefei230000 China School of Informatics Chuzhou University Anhui Province Chuzhou239000 China

The enormous computing tasks in the Mobile Edge computing (MEC) beget challenges correlated with cost, energy consumption and quality of service. However, existing studies are not optimized enough for MEC in terms of the selection of task classification and scheduling schemes. Inspired by spam classification idea, a novel task scheduling scheme is proposed for MEC via Bayesian Classifier. The MEC tasks are first categorized into three priority categories using Naive Bayes. In addition, the priority-based classification task scheduling (PCTS) scheme is proposed to schedule the classified tasks with different priorities. Finally, the experimental evaluation is conducted using three metrics that include latency, processing time, and energy consumption. Simulation results show that the proposed scheme outperforms the baseline schemes in accordance with completion time and throughout rate. © Published under licence by IOP Publishing Ltd.

关键词： Mobile edge computing

来源：评论

学校读者我要写书评

暂无评论

Effect of Genetic Algorithm in Optimizing Deep Structured Petroleum Reservoir Classifier 7

Effect of Genetic Algorithm in Optimizing Deep Structured Pe...

引用

7th international conference on computing, Communication and Security, ICCCS 2022 and 2022 4th international conference on big data and Computational intelligence, ICBDCI 2022

作者： Pandey, Rakesh Kumar Kumar, Anil Sharma, Akhilesh Kumar Sharma, Ratnesh Kumar Nguyen, Ha Huy Cuong DIT University School of Computing Department of Petroleum and Energy Studies Dehradun India Manipal University Jaipur SIT IT Department Jaipur India University of Technology Department of Computer Science Sydney Australia Viet Nam Korea University of Information and Communication Technology Da Nang City Viet Nam

ISBN: (纸本)9798350309904

Well-test analysis contributes to petroleum reservoir description for field development. The reservoir formation identification is the foremost step in characterizing petroleum reservoirs. This research aims to investigate the performance of evolutionary optimization assisted deep structured classifier to identify the homogeneous and fractured reservoirs. The classifier consists of OSTM-long short-term memory and dense neural networks. The hyper-parameters of the classifier have been fine tuned, using evolutionary optimization. The (GA)genetic algorithm conducts a rigorous problem space search to fine-tune the model. The proposed classifier has attained 95.53% accuracy in classifying the reservoirs and their external boundaries. An optimized classifier automatically detects the reservoir formations minimizing human efforts and costs. © 2022 IEEE.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Incentive-compatible intelligence Collaboration Analysis Framework Based on Blockchain and Evolutionary Game 19

Incentive-compatible Intelligence Collaboration Analysis Fra...

引用

2022 IEEE SmartWorld, 19th IEEE international conference on Ubiquitous intelligence and computing, 2022 IEEE international conference on Autonomous and Trusted Vehicles conference, 22nd IEEE international conference on Scalable computing and Communications, 2022 IEEE international conference on Digital Twin, 8th IEEE international conference on Privacy computing and 2022 IEEE international conference on Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022

作者： Xu, Zhigang Li, Qi Dong, Xinhua Han, Hongmu Yan, Zhongzhen Wang, Haitao Hubei University of Technology School of Computer Science Wuhan China Narcotics Control Bureau Public Security of Guangdong Province Guangzhou China

ISBN: (纸本)9798350346558

Collaborative intelligence data analysis can effectively dig out valuable information from massive data to support decision-making. Ensuring data credibility in collaboration under the background of big data is a crucial problem to be solved. In addition, the low willingness of analysts to share results in low efficiency of collaborative tasks. To solve the above problems, this paper proposes a blockchain-based intelligence collaborative analysis and sharing framework, ICASChain, which contains a highly trusted intelligence collaboration mechanism and a dynamically adjustable incentive mechanism. Based on Evolutionary Game Theory, this paper analyzes the evolutionary stability strategy of intelligence sharing willingness of analysts by constructing a replication dynamic equation. We use a smart contract incentive algorithm including ICASToken to dynamically regulate them to increase the proportion of users participating in intelligence sharing. Finally, the influencing factors of information sharing and the incentive effect of the incentive model are discussed through simulation experiments. The simulation results show that the proposed ICASChain has essential application value in improving the analysts' willingness to collaborate and share intelligence and the correctness of the analysis results. © 2022 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

A systematic literature review on machine learning for electricity market agent-based models

A systematic literature review on machine learning for elect...

引用

2022 IEEE international conference on big data, big data 2022

作者： Kell, Alexander J.M. McGough, A. Stephen Forshaw, Matthew Imperial College London Department of Chemical Engineering London United Kingdom Newcastle University School of Computing Newcastle United Kingdom

ISBN: (纸本)9781665480451

The electricity market has a vital role to play in the decarbonisation of the energy system. However, the electricity market is made up of many different variables and data inputs. These variables and data inputs behave in sometimes unpredictable ways which can not be predicted a-priori. It has therefore been suggested that agent-based simulations are used to better understand the dynamics of the electricity market. Agent-based models provide the opportunity to integrate machine learning and artificial intelligence to add intelligence, make better forecasts and control the power market in better and more efficient ways. In this systematic literature review, we review 55 papers published between 2016 and 2021 which focus on machine learning applied to agent-based electricity market models. We find that research clusters around popular topics, such as bidding strategies. However, there exists a long-tail of research applications that could benefit from the high intensity research from the more investigated applications. © 2022 IEEE.

关键词： Power markets

来源：评论

学校读者我要写书评

暂无评论

DBFed: Debiasing Federated Learning Framework based on Domain-Independent 9

DBFed: Debiasing Federated Learning Framework based on Domai...

引用

9th international conference on big data computing and Communications, bigCom 2023

作者： Li, Jiale Li, Zhixin Wang, Yibo Li, Yao Wang, Lei Dalian University of Technology School of Software Dalian China Fudan University School of Computer Science Shanghai China

ISBN: (纸本)9798350331240

As digital transformation continues, enterprises are generating, managing, and storing vast amounts of data, while artificial intelligence technology is rapidly advancing. However, it brings challenges in information security and data security. data security refers to the protection of digital information from unauthorized access, damage, theft, etc. throughout its entire life cycle. With the promulgation and implementation of data security laws and the emphasis on data security and data privacy by organizations and users, Privacy-preserving technology represented by federated learning has a wide range of application scenarios. Federated learning is a distributed machine learning computing framework that allows multiple subjects to train joint models without sharing data to protect data privacy and solve the problem of data islands. However, the data among multiple subjects are independent of each other, and the data differences in quality may cause fairness issues in federated learning modeling, such as data bias among multiple subjects, resulting in biased and discriminatory models. Therefore, we propose DBFed, a debiasing federated learning framework based on domain-independent, which mitigates model bias by explicitly encoding sensitive attributes during client-side training. This paper conducts experiments on three real datasets and uses five evaluation metrics of accuracy and fairness to quantify the effect of the model. Most metrics of DBFed exceed those of the other three comparative methods, fully demonstrating the debiasing effect of DBFed. © 2023 IEEE.

关键词： Sensitive data

来源：评论

学校读者我要写书评

暂无评论

Research on Classification Label Denoising Algorithm Based on Granular Ball 7

Research on Classification Label Denoising Algorithm Based o...

引用

7th international conference on Cloud computing and big data Analytics, ICCCBDA 2022

作者： Kong, Weiyu Wu, Yanmin Qi, Jinli Chen, Yanyi Chongqing Key Lab. of Comp. Sci. and Technology Chongqing University of Posts and Telecommunications ChongQing China ChongQing College of Electronic Engineering Department of Artificial Intelligence and Big Data ChongQing China Chongqing University of Posts and Telecommunications Department of Software Engineering ChongQing China

ISBN: (纸本)9781665487115

This paper presents a granular ball denoising method (GBD) which can effectively improve the accuracy and robustness of classification algorithm. GBD method first uses the self-Adaptive hypersphere to cover the data space, then eliminates the data not contained in the hypersphere and the noise data in the sphere, and finally uses only the hypersphere data for training, so as to reduce the sample data and improve the data quality. Experiments show that using the data obtained by this method for training can greatly improve the accuracy of the classification algorithm. In addition, because the hypersphere has good adaptive ability, GBD also has excellent robustness. The experiment shows that GBD sampling data training can still get good results after adding noise to the data set. Therefore, GBD is an efficient and robust denoising method. © 2022 IEEE.

关键词： Training Cloud computing data integrity Noise reduction big data Robustness Classification algorithms

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136页 << < 22 23 24 25 26 27 28 29 30 31 > >>

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：