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

11,734 篇 会议
121 篇 期刊文献
18 册 图书
1 篇 学位论文

馆藏范围

11,874 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

8,292 篇 工学
- 6,672 篇 计算机科学与技术...
- 4,205 篇 软件工程
- 1,734 篇 控制科学与工程
- 1,501 篇 信息与通信工程
- 1,423 篇 电气工程
- 1,151 篇 生物工程
- 625 篇 机械工程
- 534 篇 生物医学工程（可授...
- 434 篇 交通运输工程
- 397 篇 动力工程及工程热...
- 395 篇 电子科学与技术（可...
- 374 篇 光学工程
- 330 篇 网络空间安全
- 320 篇 石油与天然气工程
- 297 篇 安全科学与工程
- 239 篇 仪器科学与技术
3,520 篇 理学
- 2,157 篇 数学
- 1,228 篇 生物学
- 576 篇 物理学
- 575 篇 统计学（可授理学、...
- 406 篇 系统科学
- 266 篇 化学
2,086 篇 管理学
- 1,412 篇 管理科学与工程(可...
- 775 篇 图书情报与档案管...
- 597 篇 工商管理
662 篇 医学
- 485 篇 临床医学
- 425 篇 基础医学(可授医学...
- 299 篇 药学(可授医学、理...
- 267 篇 公共卫生与预防医...
431 篇 教育学
- 426 篇 教育学
225 篇 法学
211 篇 经济学
179 篇 农学
16 篇 文学
16 篇 军事学
15 篇 艺术学
2 篇 哲学

主题

890 篇 deep learning
809 篇 machine learning
711 篇 optimization
401 篇 accuracy
321 篇 reinforcement le...
279 篇 feature extracti...
228 篇 support vector m...
222 篇 computational mo...
219 篇 predictive model...
211 篇 training
200 篇 real-time system...
184 篇 neural networks
179 篇 particle swarm o...
162 篇 genetic algorith...
159 篇 data mining
151 篇 internet of thin...
149 篇 learning systems
149 篇 artificial intel...
142 篇 machine learning...
136 篇 data models

机构

60 篇 chitkara univers...
15 篇 school of comput...
15 篇 beijing universi...
14 篇 national univers...
14 篇 the islamic univ...
12 篇 tianjin universi...
12 篇 uttaranchal inst...
12 篇 national univers...
12 篇 weifang engineer...
11 篇 college of techn...
11 篇 misr internation...
11 篇 beijing institut...
10 篇 pune
10 篇 bengaluru
10 篇 uttaranchal univ...
10 篇 school of comput...
10 篇 school of comput...
9 篇 phaethon centre ...
9 篇 maharishi school...
9 篇 school of electr...

作者

17 篇 hassanien aboul ...
16 篇 lima jose
12 篇 wang lei
12 篇 yang bo
12 篇 li bo
11 篇 pereira ana i.
11 篇 wang wei
10 篇 malik bader alaz...
10 篇 liu yan
10 篇 chen xin
9 篇 li yan
8 篇 li xin
8 篇 li yang
8 篇 wang jing
8 篇 li li
8 篇 zhang chao
8 篇 liu yang
8 篇 li hao
8 篇 li xiang
7 篇 nagaraj p.

语言

10,996 篇 英文
849 篇 其他
64 篇 中文
2 篇 西班牙文

检索条件"任意字段=3rd Conference on Learning and Intelligent Optimization"

共 11874 条记录，以下是41-50 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：

ASBO-MAT-BiLSTM: Social Media Network Anomaly Detection using Optimized Multihead Attention Transformer based Model 3

ASBO-MAT-BiLSTM: Social Media Network Anomaly Detection usin...

引用

3rd International conference on intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Lunawat, Sonali Rao, Jyoti Patil, Pramod Dr. D. Y. Patil Institute of Technology Pimpri Pune India

ISBN: (纸本)9798331527549

Currently, attacks in the networks are the most vital issue in modern society and the networks from minor to huge networks are susceptible to network threats. Various approaches exist with several advantages and limitations in detecting anomaly, such as computational complexity, overfitting, low level of accuracy in detection, and so on. To overcome these issues and detect network anomaly effectively Adaptive Secretary Bird optimization algorithm (ASBO) is integrated with the RAnked Minority Oversampling in Boosting (RAMOB) model to resolve the issue of data imbalance through making the data in a balanced manner. The Multihead Attention Transformer (MAT) mechanism and ASBO algorithm enable the BiLSTM model to effectively detect anomaly by solving the issues of overfitting and complexities in terms of both time and computation. The experimental outcomes display that the ASBO-MAT-BiLSTM model reaches an accuracy of 97.116% using NSL-KDD Dataset and accuracy of 96.54%, using CIC-IDS2017 Dataset, which reveals that our model attains higher efficiency in detecting anomalies in the networks. © 2025 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Research on Short-term Electricity Demand Forecasting Based on Deep learning Algorithms 24

Research on Short-term Electricity Demand Forecasting Based ...

引用

3rd International conference on Artificial Intelligence and intelligent Information Processing, AIIIP 2024

作者： Fan, Zhuoni Gao, Yuan College of Economics and Management Beijing Jiaotong University Beijing China Shandong Energy Group Materials Co. Ltd. Luzhong Branch Shandong Taian China

ISBN: (纸本)9798400707308

This paper introduces an advanced short-term electricity demand forecasting model based on Recurrent Neural Networks (RNN) combined with Long Short-Term Memory (LSTM) units. This hybrid model effectively captures the temporal dynamics in electricity consumption, incorporating features such as past energy use, temperature, humidity, and calendar variables. By utilizing a rolling prediction technique, the model addresses long-term prediction challenges and enhances accuracy. Extensive model evaluation shows a marked reduction in error metrics, including Mean Absolute Error and Root Mean Squared Error. The proposed method demonstrates significant potential for real-time energy demand forecasting, supporting grid optimization and energy management. This approach highlights the model’s applicability in smart grid systems, providing more reliable predictions crucial for operational efficiency and sustainability. © 2024 Copyright held by the owner/author(s).

关键词： Demand response

来源：评论

学校读者我要写书评

暂无评论

Computer-Aided Railway Operations Human Resources optimization and Performance Evaluation 24

Computer-Aided Railway Operations Human Resources Optimizati...

引用

3rd International conference on Algorithms, Data Mining, and Information Technology, ADMIT 2024

作者： Feng, Xiaojie Shuohuang Railway Development Co. Ltd. Chengdu China

ISBN: (纸本)9798400718120

With the increasingly complex business environment, the rational allocation of human resources and the improvement of personnel utilization efficiency have become key factors for enterprises to maintain competitiveness. In this paper, a computer-aided human resources optimization solution is proposed to address this issue. This solution establishes a scientific optimization model, designs efficient hybrid intelligent optimization algorithms, and develops a complete optimization management system. Through in-depth analysis of human resources and business data, combined with actual enterprise constraints, the system can automatically solve the optimal human resource allocation scheme, providing decision support for enterprise implementation. In trials conducted in multiple enterprises, this solution significantly optimized the allocation of human resources, greatly improved resource utilization efficiency, and achieved significant economic benefits. © 2024 Copyright held by the owner/author(s).

关键词： Human resources optimization

来源：评论

学校读者我要写书评

暂无评论

Research on Multi-Aircraft Trajectory Planning Based on Reinforcement learning 24

Research on Multi-Aircraft Trajectory Planning Based on Rein...

引用

3rd International conference on Artificial Intelligence and intelligent Information Processing, AIIIP 2024

作者： Zhang, Zhaorui Dai, Wenfei Han, Hongming Nanjing University of Aeronautics and Astronautics Jiangsu Nanjing China

ISBN: (纸本)9798400707308

This study explores the application of deep reinforcement learning algorithms in the field of air traffic, particularly focusing on intelligent trajectory planning for multiple aircraft. By using the K-means clustering algorithm to identify trajectory patterns in the Shanghai terminal area and employing a grid method for three-dimensional airspace modeling, the trajectory planning space for aircraft was significantly reduced. Finally, the DDQN algorithm was used to achieve trajectory planning for aircraft within the Shanghai terminal area. The research covers terminal area airspace modeling, trajectory pattern recognition, and aircraft trajectory planning. By configuring a simulation environment based on the Shanghai terminal area airspace model, the effectiveness of the DDQN algorithm in improving the efficiency and safety of autonomous aircraft scheduling was validated, demonstrating the great potential of deep reinforcement learning algorithms in solving multi-aircraft trajectory planning problems. © 2024 Copyright held by the owner/author(s).

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Machine learning Algorithms for Disease Prediction using Medical Datasets 3

Comparative Analysis of Machine Learning Algorithms for Dise...

引用

3rd International conference on intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Roopa, C. Latha, R.S. Dhavamani, M. Bommisrilekkhaa, G. Angel Shalini, P. Dhanyajothi, R. Department of Computer Science and Engineering Kongu Engineering College Tamilnadu Erode India Department of Artificial Intelligence Kongu Engineering College Tamilnadu Erode India Department of Mathematics Kongu Engineering College Tamilnadu Erode India

ISBN: (纸本)9798331527549

Application of machine learning in the analysis of medical data can be said to be one of the current transformations happening within the healthcare fraternity. This paper highlights several ways in which various machine learning techniques can be used for gaining valuable insight into disparate types of medical data, such as patient records or genetic information, toward further clinical decision-making with a view to better prediction of diseases or strategies related to personalized medicine. The study critically evaluated various algorithms by considering their performances, suitability with regard to certain medical datasets they would be set upon to analyze, and to interpret the performance, particularly within the supervised learning frameworks. It talks about methodologies through which feature selection can take place to make sure that there is effective model development. Consequential applications in early disease detection as well as the optimization of their treatments are further emphasized, representing great potential for massive improvements in their recovery outcomes. The results highlight how far reaching data-driven approaches can affect the future of healthcare. It is envisioned that, with the use of such methods, the paper foresees a paradigm shift in disease diagnosis and treatment for personalized medical care and improved health outcomes. © 2025 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Maximizing Throughput and Minimizing Latency: Evolutionary Algorithms for Optimizing Wireless Cellular Networks 3

Maximizing Throughput and Minimizing Latency: Evolutionary A...

引用

3rd International conference on intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Pechetti, Jyoshitha Yadav, Sneha Tarunya, G. Rajagopal, Shinu M. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

In the rapidly evolving world of wireless cellular network, optimizing key parameters like data throughput and latency is of critical importance for ensuring high quality communication services. The proposed presents a novel approach to multi-objective optimization to enhance overall network performance using Genetic Algorithms (GA), Pareto, and Particle Swarm optimization (PSO). By employing optimization algorithms, a balance is sought in terms of trade-off of other parameters while maximizing data throughput and minimizing latency. Simulation layers indicate the comparative study further solidifies the efficacy of the value of evolutionary algorithms in optimizing wireless networks to satisfy the growing needs of high speed and less latency services in today’s communication landscape. © 2025 IEEE.

关键词： optimization algorithms

来源：评论

学校读者我要写书评

暂无评论

Augmented Reality (AR) and Virtual Reality (VR) for Personalized learning 3

Augmented Reality (AR) and Virtual Reality (VR) for Personal...

引用

3rd International conference on intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Gaikwad, Aditya Rahul Gaikwad, Rohan Maruti Jodh, Dasharathraje Naganath Khiani, Simran Department of Computer Engineering G. H Raisoni College of Engineering and Management Pune India

ISBN: (纸本)9798331527549

To develop a specific learning environment using augmented reality (AR) and virtual reality (VR) technology, we create immersive and interactive educational experiences that enhance engagement, improve understanding of complex concepts, and cater to diverse learning styles for students. The system will be able to meet the needs of each learner by gathering data on their learning objectives, preferences, and past knowledge. Interactive multiple-choice questions will be used to evaluate students' performance and identify areas for development. Based on the findings, the website will recommend relevant study guides and classes. AR and VR technology will be used to develop immersive learning environments that include interactive simulations, 3D visualizations, and collaborative virtual worlds. To improve learning results and student engagement, the platform's architecture will prioritize data security, accessibility, and usability. © 2025 IEEE.

关键词： Virtual environments

来源：评论

学校读者我要写书评

暂无评论

A Preprocessing Algorithm to Identify Errors in Datasets for AutoML 3

A Preprocessing Algorithm to Identify Errors in Datasets for...

引用

3rd International conference on intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Shivappa, Nagesha JSS Academy of Technical Education Bengaluru India

ISBN: (纸本)9798331527549

Machine learning algorithms need a dataset for training and performance evaluation. Usually, the dataset samples collected are incomplete in many aspects. There may be an incorrect recording of one or more features values, an unknown value (empty), an incorrect symbol for categorical features, etc. The dataset must be corrected (preprocessed) before presenting to the machine learning algorithm for training and performance evaluation. But datasets usually consist of a large number of samples and hence manually searching for defects is time-consuming and difficult if not impossible. This paper presents an algorithm to preprocess datasets to identify and list errors in the datasets. The effort is in the direction of automated machine learning (autoML) pipeline development to ease the use of ML by non-experts. The algorithm is tested with a dataset that has all kinds of data types and errors in the dataset are listed. © 2025 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Skin cancer severity analysis and prediction framework based on deep learning 24

Skin cancer severity analysis and prediction framework based...

引用

3rd International conference on Artificial Intelligence and intelligent Information Processing, AIIIP 2024

作者： Huang, Ruijie Wu, Haoran AI of FST Beijing Normal University-Hong Kong Baptist University United International College Guangdong Zhuhai China

ISBN: (纸本)9798400707308

This paper provides a Convolutional Neural Network (CNN) based skin cancer detection model that categorizes skin lesions as benign or malignant. To increase its resilience, the model makes use of picture enhancing strategies such data augmentation and normalization. The approach automatically collects characteristics from pictures via the construction of a deep convolutional network, hence enabling efficient categorization. The dataset was divided into training and validation sets inside the experimental framework, using convolutional layers, max pooling, and fully connected layers—common deep learning architectures. We used the Adam optimizer for performance optimization and binary cross-entropy as the loss function in a binary classification challenge. We assessed the model’s performance during training by looking at parameters like accuracy and AUC (Area Under the Curve). The testing results show that the model detects skin cancer with excellent accuracy and reliability;on the test set, both accuracy and AUC approach substantial values. In addition, we used a confusion matrix to determine the model’s sensitivity, specificity, and positive predictive value, which allowed for a more thorough examination of its categorization capabilities. The results indicate that the CNN-based model has a great deal of promise for use in skin cancer diagnosis, providing a theoretical framework for later practical application. © 2024 Copyright held by the owner/author(s).

关键词： Benign and malignant classification

来源：评论

学校读者我要写书评

暂无评论

Deep learning-Based Automatic Identification System for Marine Plankton 24

Deep Learning-Based Automatic Identification System for Mari...

引用

3rd International conference on Algorithms, Data Mining, and Information Technology, ADMIT 2024

作者： Xiang, Su Shandong University of Science and Technology Shandong Qingdao China

ISBN: (纸本)9798400718120

Due to their diverse species and complex morphology, the automatic identification of marine plankton has always been a challenging task. In response to this problem, this study proposes an innovative deep learning-based intelligent identification system. The system integrates advanced computer vision and artificial intelligence technologies, possessing the capability of automatic feature extraction and pattern recognition. We extensively collected marine sampling data and combined it with public datasets to construct a large-scale database containing 200 species of plankton and 500,000 images. Through the training and optimization of convolutional neural network models, the system demonstrates outstanding classification performance of 94.2% on the test set. Not only does the system outperform traditional methods in accuracy, but its inference speed has also been optimized through model compression and parallel computing, capable of processing 620 images per second. By deploying containerization and automatic scaling strategies, the system ensures high availability. This research provides strong technical support for marine ecological conservation, fisheries management, and other related fields. © 2024 Copyright held by the owner/author(s).

关键词： Convolutional neural networks

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 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：