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

13,239 篇 会议
188 册 图书
157 篇 期刊文献

馆藏范围

13,583 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

9,037 篇 工学
- 7,539 篇 计算机科学与技术...
- 4,285 篇 软件工程
- 1,624 篇 信息与通信工程
- 1,528 篇 电气工程
- 1,231 篇 控制科学与工程
- 962 篇 生物工程
- 513 篇 机械工程
- 500 篇 生物医学工程（可授...
- 470 篇 电子科学与技术（可...
- 461 篇 动力工程及工程热...
- 326 篇 光学工程
- 308 篇 交通运输工程
- 294 篇 安全科学与工程
- 267 篇 材料科学与工程（可...
- 248 篇 化学工程与技术
3,512 篇 理学
- 2,202 篇 数学
- 1,058 篇 生物学
- 604 篇 物理学
- 582 篇 统计学（可授理学、...
- 472 篇 系统科学
- 241 篇 化学
1,861 篇 管理学
- 1,292 篇 管理科学与工程(可...
- 681 篇 图书情报与档案管...
- 542 篇 工商管理
595 篇 医学
- 497 篇 临床医学
- 406 篇 基础医学(可授医学...
- 223 篇 药学(可授医学、理...
306 篇 教育学
- 296 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

1,319 篇 optimization
1,089 篇 machine learning
1,031 篇 deep learning
501 篇 accuracy
462 篇 reinforcement le...
329 篇 computational mo...
310 篇 machine learning...
290 篇 training
286 篇 feature extracti...
279 篇 support vector m...
255 篇 predictive model...
248 篇 neural networks
239 篇 real-time system...
210 篇 genetic algorith...
204 篇 adversarial mach...
168 篇 convolutional ne...
161 篇 particle swarm o...
154 篇 learning algorit...
143 篇 artificial intel...
142 篇 internet of thin...

机构

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

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
9 篇 varshney neeraj
8 篇 yang tianbao
8 篇 neeraj varshney
8 篇 r. santhana kris...
8 篇 misra sanjay
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

语言

11,966 篇 英文
1,588 篇 其他
137 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 13584 条记录，以下是731-740 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：

the Enhanced Optimal Path Selection for WSN using Hybrid Ant Colony optimization Technique 4

The Enhanced Optimal Path Selection for WSN using Hybrid Ant...

引用

4th IEEE Annual Flagship India Council international Subsections conference, INDISCON 2023

作者： Mittal, Vipin Desai, Meena School of Engineering & Technology Iimt University Department of Electrical & Electronics Engineering Uttar Pradesh Meerut India Isme - School of Management & Entrepreneurship Atlas Skill Tech University Maharashtra Mumbai India

ISBN: (纸本)9798350333558

Network routing is a critical component of Wireless Sensor Networks (WSNs), and the process of finding the optimal path or set of paths between two nodes such that certain criteria are met, also known as routing, is of utmost importance in efficient WSNs. Hybrid Ant Colony optimization (HACO) is a recently proposed optimization technique that combines both Ant Colony optimization (ACO) and Evolutionary algorithms (EA) to address the issue of WSN routing. the technique is primarily used to find the optimal routing path from the source node to the destination node, and is tailored to the WSNs environment due to its self-organizing properties, such as adaptivity and scalability. HACO for WSN routing primarily seeks to reduce both transmission cost and latency by finding near-optimum solutions and spanning very large search spaces more quickly than ACO or EA alone. HACO also offers better scalability than other methods due to its ability to spread out the computation workload under resource constraints. Hybrid ant colony optimization for WSN routing has been found to significantly improve the performance of WSNs as compared to traditional routing solutions such as Bellman-Ford or Dijkstra algorithms, and offers improvements in both routing efficiency and cost savings. © 2023 IEEE.

关键词： Ant colony optimization

来源：评论

学校读者我要写书评

暂无评论

Decentralized Satellite Federated learning via Intra- and Inter-Orbit Communications 59

Decentralized Satellite Federated Learning via Intra- and In...

引用

59th Annual IEEE international conference on Communications (IEEE ICC)

作者： Zhou, Fangtong Wang, Zhibin Shi, Yuanming Zhou, Yong ShanghaiTech Univ Sch Informat Sci & Technol Shanghai 201210 Peoples R China

ISBN: (纸本)9798350304060;9798350304053

Satellite federated learning (SFL) emerges as a promising approach to exploit computing and data resources within low Earth orbit (LEO) satellite constellations for supporting intelligent applications while maintaining privacy protection. Most of the existing works of SFL consider a ground station as the central server to aggregate model parameters transmitted from satellites. However, the intermittent connection between satellites and ground stations leads to overlong convergence time. In this paper, we propose a novel decentralized SFL in the Walker-Delta constellation, where satellites communicate with nearby satellites in the same or different orbital planes through inter-satellite links (ISLs). We formulate a mixed combinatorial optimization problem that involves the joint optimization of power control, bandwidth allocation, and routing selection of each satellite to minimize the energy consumption in SFL. A joint resource allocation and routing selection (JRARS) algorithm is subsequently developed to solve the proposed optimization problem. Results show that our proposed decentralized SFL framework outperforms other SFL frameworks in terms of convergence time and accuracy. We also show that our proposed JRARS algorithm consumes much lower energy consumption than the baseline algorithms when the model converges.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Towards a Lightweight Detection System Leveraging Ranking Techniques with Wrapper Feature Selection Algorithm for Selective Forwarding Attacks in Low power and Lossy Networks of IoTs 4

Towards a Lightweight Detection System Leveraging Ranking Te...

引用

4th international conference on Emerging Smart Technologies and applications (eSmarTA)

作者： Al-Amiedy, Taief Alaa Anbar, Mohammed Belaton, Bahari Bahashwan, Abdullah Ahmed Abualhaj, Mosleh M. Univ Sains Malaysia Natl Adv IPv6 Nav6 Ctr Gelugor 11800 Malaysia Univ Sains Malaysia Sch Comp Sci Gelugor 11800 Penang Malaysia Al Ahliyya Amman Univ Dept Networks & Cybersecur Amman Jordan

ISBN: (纸本)9798350354140;9798350354133

the advent of the Internet of things (IoT) marks a significant shift in networking paradigms, offering numerous advantages across various applications owing to advancements in embedded system technologies and IPv6 compression. this evolution enables the integration of IP functionalities within Low Power and Lossy Networks (LLNs). However, as LLNs become increasingly integral to IoT ecosystems, they become prime targets for cyber threats. While Machine learning (ML) has demonstrated potential in identifying irregularities within the Routing Protocol for LLNs (RPL), it encounters issues, including the handling of unbalanced datasets, identifying critical features of attacks, long processing times, and substantial power usage. To address the preceding issues, this study introduces a lightweight detection system encompassing three stages: data preparation, a lightweight feature selection mechanism, and Random Forest-based selective forwarding attack detection. the proposed system is evaluated using a grid- based RPL dataset under three distinct scenarios-varying by the location of the attacking node concerning the LLN's root node. the findings demonstrate that the system performs optimally when the attacker is positioned midway to the root node, achieving accuracy, precision, recall, and F-measure scores of 86.2%, 87%, 84.3%, and 85.6%, respectively. the outcomes suggest that this lightweight approach not only surpasses existing ML techniques in terms of execution speed and resource efficiency but also in the number of features required and overall detection performance, establishing its efficacy in combating Selective Forwarding (SF) attacks in LLNs.

关键词： Low power and Lossy Network Internet of things Lightweight IDS Selective Forwarding PSO Metaheuristic optimization Feature Selection

来源：评论

学校读者我要写书评

暂无评论

An Efficient ODR for Computer Night Vision Using Multi-Scale Retinex Network-Aided Enhanced Images 4

An Efficient ODR for Computer Night Vision Using Multi-Scale...

引用

4th international conference on Power, Energy, Control and Transmission Systems, ICPECTS 2024

作者： Charles Prabu, V. Pandiaraja, P. Sathiyamoorthi, V. Durgadevi, P. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India Government Polytechnic College Department of Computer Engineering Baisuhalli Tamilnadu Dharmapuri India Srm Institute of Science and Technology Department of Computer Science and Engineering Vadapalani Campus Tamilnadu Chennai India

ISBN: (纸本)9798331508845

In the current scenario, recognizing various objects and tracking their movements in the real-time surveillance footage is the most difficult task. To detect objects, a combination of image processing and computer vision algorithms is utilized. Computer-vision based automatic human activity recognition from surveillance video can be utilized for applications such as the identification of violent acts and the study of human behavior. Consequently, this work implements a new "Object Detection and Recognition (ODR)"model for computer night vision utilizing a deep learning technique. In order to improve the supplied input image, the combined images are first transmitted to the "Multi-scale Retinex (MSR)"model. the You Only Look Once Version 7 (YoloV7) model uses the improved image from MSR as input to identify and recognize things. After conducting experiments, the implemented ODR model on the ExDark Dataset obtained an efficiency of 94.8%. © 2024 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Identification of an Efficient Machine learning Algorithm for the Prediction of Customer Churn: A Case Analysis of a Business-to-Consumer (B2C) Dairy Company for Customer Retention Strategy 4

Identification of an Efficient Machine Learning Algorithm fo...

引用

4th international conference on Innovative Practices in Technology and Management, ICIPTM 2024

作者： Faisal, A. Mohammed Rajkiran, V. Singh, K. Sankar Elantheraiyan, P. Kamalakhannan, S.K. Rajalakshmi School of Business Department of Operations & Analytics Chennai India Technology & Advance Studies School of Management Studies Vels Institute of Science Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Management Studies Chennai India Saveetha School of Law Department of Management Studies Chennai India

ISBN: (纸本)9798350307757

Machine learning algorithms can be applied to real-life applications, such as customer churn rates for dairy products, which are part of the business-to-consumer (B2C) model, to create a strong customer retention strategy. the ultimate objective is to identify an efficient machine learning algorithm that may be utilized for predicting consumer churn in dairy-based products. Following the exploratory data analysis (EDA) phase, churn prediction models are constructed using machine learning algorithms such as logistic regression, random forest, support vector machine, K-nearest neighbor (KNN), decision tree classifier, and Gaussian naive bayes. the Kaplan-Meier curve, which is based on the customer lifetime value (CLV), is used to understand the churn behavior of the customers. Two binary classifier models are chosen for further study: random forest and logistic regression, determined by the area under the receiver operating characteristic curve (AUROC). Comparing the random forest to the logistic regression, the random forest performs better overall (87.26%), with precision (85.44%), recall (88%), and F1 score (86.7%). the random forest classifier has an AUC value of 95%, which is higher than the AUC score of 93% for the refined logistic regression model, as seen by the ROC graph. In comparison to the logistic regression, the random forest classifier is doing rather well on this binary class classification task based on the confusion matrix and ROC graph. thus, the random forest classifier is considered to be the most effective one for dairy products. © 2024 IEEE.

关键词： Logistic regression

来源：评论

学校读者我要写书评

暂无评论

Stress Detection During Social Interactions with Natural Language Processing and Machine learning 4

Stress Detection During Social Interactions with Natural Lan...

引用

4th international conference on Expert Clouds and applications, ICOECA 2024

作者： Singh, Manish Kumar Kumar, Sunil University Institute of Sciences Chandigarh University Department of Mathematics Gharuan Punjab Mohali India

ISBN: (纸本)9798350385793

the field of Natural Language Processing (NLP) is witnessing a growing recognition of the significance of investigating stress-related phenomena. this research study proposes a new framework to address the diagnostic challenges associated with mental health conditions such as anxiety, depression, and stress, which can worsen if left unaddressed. Within this research study, social media postings and comments are used to enhance sentiment and emotion analysis for assessing individuals' stress levels. Specifically, text analysis of social media data, including Twitter tweets, serves as a pivotal application. the proposed system is implemented by employing a combination of Machine learning (ML), Natural Language Processing (NLP), and Deep learning (DL) methodologies. the proposed system utilizes Convolutional Neural Network (CNN), BERT transfer learning techniques, as well as Machine learning (ML) algorithms such as Naive Bayes, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN). this study aims to predict five distinct emotional categories: 'Happy, ' 'Angry, ' 'Depression, ' 'Sad, ' and 'Fear.' Remarkably, the proposed system has achieved an accuracy and F1 score exceeding 93%, outperforming the performance of other existing human emotion recognition systems. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Innovization-based Evolutionary Large-Scale Multiobjective optimization 6

Innovization-based Evolutionary Large-Scale Multiobjective O...

引用

6th international conference on Data-Driven optimization of Complex Systems (DOCS)

作者： Liu, Songbai Yan, Qianqiang Wang, Zeyi Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen Peoples R China

ISBN: (纸本)9798350377859;9798350377842

How to handle the high dimensional search space effectively is a burning research question in evolutionary computation when solving large-scale multiobjective optimization problems. To alleviate it, we propose a new evolutionary algorithm with a tactic of innovization-based representation learning, which aims to discover innovative solution principles from compressed representations. Specifically, a neural net, including an encoder and a decoder, is iteratively learned to transform input solutions into the predictions that dominate them. the encoder thus can capture their compressed representations that retain the information necessary for making good predictions. the decoder can create innovative promising solutions from newly explored representations by evolutionary search. Finally, the proposed algorithm is tested on synthetic and real-world benchmarks with the dimension of variables up to 10(4). Comparison results show the superior performance of the proposed optimizer in solving these benchmarks within 10(5) function evaluations.

关键词： Evolutionary algorithms Large-Scale Multiobjective optimization Innovization Representation learning

来源：评论

学校读者我要写书评

暂无评论

Multiple Greedy Quasi-Newton Methods for Saddle Point Problems 6

Multiple Greedy Quasi-Newton Methods for Saddle Point Proble...

引用

6th international conference on Data-Driven optimization of Complex Systems (DOCS)

作者： Xiao, Minheng Bo, Shi Wu, Zhizhong Ohio State Univ Dept Integrated Syst Engn Columbus OH 43210 USA Boston Univ Dept Math & Stat Boston MA USA Univ Calif Berkeley Coll Engn Berkeley CA USA

ISBN: (纸本)9798350377859;9798350377842

this paper introduces the Multiple Greedy Quasi-Newton (MGSR1-SP) method, a novel approach to solving strongly-convex-strongly-concave (SCSC) saddle point problems. Our method enhances the approximation of the squared indefinite Hessian matrix inherent in these problems, significantly improving both stability and efficiency through iterative greedy updates. We provide a thorough theoretical analysis of MGSR1-SP, demonstrating its linear-quadratic convergence rate. Numerical experiments conducted on AUC maximization and adversarial debiasing problems, compared with state-of-the-art algorithms, underscore our method's enhanced convergence rate. these results affirm the potential of MGSR1-SP to improve performance across a broad spectrum of machine learning applications where efficient and accurate Hessian approximations are crucial.

关键词： artificial intelligence saddle point problems quasi-Newton methods optimization

来源：评论

学校读者我要写书评

暂无评论

ML-assisted optimization of Securities Lending 23

ML-assisted Optimization of Securities Lending

引用

4th ACM international conference on AI in Finance (ICAIF)

作者： Prasad, Abhinav Arunachalam, Prakash Motamedi, Ali Bhattacharya, Ranjeeta Liu, Beibei McCormick, Hays Skip Xu, Shengzhe Muralidhar, Nikhil Ramakrishnan, Naren Bank New York Mellon New York NY 10166 USA Virginia Tech Comp Sci Arlington VA USA Stevens Inst Technol Comp Sci Hoboken NJ USA

ISBN: (纸本)9798400702402

this paper presents an integrated methodology to forecast the direction and magnitude of movements of lending rates in security markets. We develop a sequence-to-sequence (seq2seq) modeling framework that integrates feature engineering, motif mining, and temporal prediction in a unified manner to perform forecasting at scale in real-time or near real-time. We have deployed this approach in a large custodial setting demonstrating scalability to a large number of equities as well as newly introduced IPO-based securities in highly volatile environments.

关键词： Securities Lending Sequence-to-Sequence Modeling Motif Mining Deep learning

来源：评论

学校读者我要写书评

暂无评论

Machine learning applications: Case of Data Clustering using NLP with Supervised learning Techniques 14

Machine Learning Applications: Case of Data Clustering using...

引用

Decima Cuarta Conferencia Iberoamericana de Complejidad, Informatica y Cibernetica, CICIC 2024 en el contexto de the 15th international Multi-conference on Complexity, Informatics and Cybernetics, IMCIC 2024 - 14th Ibero-American conference on Complexity, Informatics and Cybernetics, CICIC 2024 in the context of the 15th international Multi-conference on Complexity, Informatics and Cybernetics, IMCIC 2024

作者： Sangacha-Tapia, Lady González-Cañizalez, Yomar Manrique-Suarez, Rubén Estupiñan-Vera, Galo Unidad de Proyectos de Investigación I+D+i Instituto Superior Tecnológico del Azuay De Superior Universitario Cuenca Ecuador Facultad de Ingeniería Industrial Universidad de Guayaquil Guayaquil Ecuador

ISBN: (纸本)9781950492763

the work developed aims to identify new applications of machine learning knowledge, such as computer science and engineering for industry, possible is by grouping bibliographic data where natural language texts must process through supervised machine learning, this branch of intelligence groups data data to classify the text and finally label it in binary form, being applied in the case of optimization algorithms oriented to operations research. the method included bibliographic data mining of more than 1000 records published in the relevant database as (Scopus, Web of Science, etc.), following the methodology SEMMA, for identifying patterns in data and predicting the trend in Machine learning applications in industry with natural language processing, using a supervised learning algorithm for the optimization of the binary classification model by code with its Python programming language, used in data science. the application of the model showed 99% assertive result of recall in the prediction model. © 2024 Memorias de la Conferencia Iberoamericana de Complejidad, Informatica y Cibernetica, CICIC. All rights reserved.

关键词： Adversarial machine learning

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 << < 70 71 72 73 74 75 76 77 78 79 > >>

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：