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

140 篇 会议
5 篇 期刊文献

馆藏范围

145 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

115 篇 工学
- 60 篇 计算机科学与技术...
- 38 篇 软件工程
- 37 篇 控制科学与工程
- 33 篇 电气工程
- 20 篇 信息与通信工程
- 18 篇 动力工程及工程热...
- 14 篇 材料科学与工程（可...
- 10 篇 机械工程
- 8 篇 化学工程与技术
- 8 篇 生物工程
- 6 篇 力学（可授工学、理...
- 6 篇 光学工程
- 6 篇 电子科学与技术（可...
- 6 篇 建筑学
- 5 篇 仪器科学与技术
- 5 篇 水利工程
- 4 篇 土木工程
- 4 篇 生物医学工程（可授...
- 4 篇 安全科学与工程
- 3 篇 交通运输工程
55 篇 理学
- 29 篇 数学
- 12 篇 物理学
- 10 篇 统计学（可授理学、...
- 9 篇 生物学
- 4 篇 化学
- 4 篇 大气科学
- 4 篇 系统科学
- 3 篇 天文学
23 篇 管理学
- 21 篇 管理科学与工程(可...
- 7 篇 工商管理
2 篇 经济学
2 篇 法学
2 篇 医学
1 篇 教育学
1 篇 农学
1 篇 军事学

主题

4 篇 power quality
4 篇 reactive power
4 篇 renewable energy...
3 篇 genetic algorith...
3 篇 mathematical mod...
3 篇 quality control
2 篇 internet of thin...
2 篇 model predictive...
2 篇 deep learning
2 篇 matlab
2 篇 long short-term ...
2 篇 face recognition
2 篇 inverters
2 篇 quality of servi...
2 篇 wind turbines
2 篇 data mining
2 篇 control systems
2 篇 cloud manufactur...
2 篇 decentralized co...
2 篇 accuracy

机构

4 篇 school of contro...
3 篇 key lab of urban...
3 篇 jiangsu province...
3 篇 state grid shand...
2 篇 hubei key labora...
2 篇 china automotive...
2 篇 school of comput...
2 篇 beijing advanced...
2 篇 beijing key labo...
2 篇 school of automa...
1 篇 automation engin...
1 篇 madhav universit...
1 篇 study program of...
1 篇 aeronautics engi...
1 篇 deptt. of comp s...
1 篇 department of li...
1 篇 beijing univ tcm...
1 篇 dept of computer...
1 篇 guilin universit...
1 篇 hefei university...

作者

3 篇 duan xuting
3 篇 guo peng
3 篇 wang wenyang
3 篇 rong hui
3 篇 tian daxin
3 篇 zhang haijun
2 篇 hasan mashhood
2 篇 asit mohanty
2 篇 zheng kunxian
2 篇 pandey jai praka...
2 篇 li cong
2 篇 chauhan rajeev k...
2 篇 xie xiaolan
1 篇 ying shang
1 篇 hu yao-cong
1 篇 xu jin-meng
1 篇 baharom rahimi
1 篇 khumaidi a.
1 篇 du xiaoming
1 篇 ravindra kurup

语言

143 篇 英文
2 篇 其他

检索条件"任意字段=1st International Conference on Advanced Algorithms and Control Engineering, ICAACE 2018"

共 145 条记录，以下是1-10 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：

Optimizing DFIG Wind Farms: advanced controls and Energy storage Integration 1

Optimizing DFIG Wind Farms: Advanced Controls and Energy Sto...

引用

1st international conference on Cognitive, Green and Ubiquitous Computing, IC-CGU 2024

作者： Das, Sachin Samanta, Indu Sekhar Dash, Rudranarayan Pati, Abhilash Kundu, Subhasree Panigrahi, Amrutanshu School of Electrical Engineering KIIT University Silicon Institute of Technology Bhubaneswar India Department of CSE Bhubaneswar India School of Electrical Engineering KIIT University Bhubaneswar India

ISBN: (纸本)9798350361780

This research study introduces a new way to optimize wind farms that use Doubly Fed Induction Generators (DFIGs) by combining energy storage systems with improved control algorithms. The study takes into account the fact that wind energy is not constant and uses adaptive control, model predictive control (MPC), and fuzzy logic control (FLC) to improve power quality, fault ride-through capability, and dynamic responsiveness. This study summarizes the current research on DFIG-based wind farms and discusses their benefits, drawbacks, and potential improvements. To lessen the impact of wind power's intermittency, it presents new control algorithms and investigates the possibility of incorporating energy storage like batteries or supercapacitors. The article delves into the best ways to maximize the usefulness of energy storage devices in a wind farm, including their size and placement. © 2024 IEEE.

关键词： Model predictive control

来源：评论

学校读者我要写书评

暂无评论

Enhanced Security in Payment Gateways Through Face Detection: An advanced Approach Using DenseNet 121- BiLstM Models 1

Enhanced Security in Payment Gateways Through Face Detection...

引用

1st IEEE international conference on Electronics, Computing, Communication and control Technology, ICECCC 2024

作者： Gowsic, K. Sowmiya, M. Nirmala Devi, M. Chauhan, Amit Arul Mary Rexy, V. Singh, Dharmendra Department of Computer Science and Engineering Namakkal India Department of Life Sciences Karnataka Bengaluru India St. Martin's Engineering College Department of English Secunderabad India Saveetha College of Liberal Arts and Sciences SIMATS Department of Commerce Kuthambakkam India School of Management Sciences Department of Applied Science Lucknow India

ISBN: (纸本)9798350371802

Because it is one of the most promising applications of image analysis, face recognition has been the subject of intense research and development for many decades. Many modern identification and verification requirements have found a potential new home with the introduction of face recognition (FR) technology. Facial recognition is just one of numerous uses for biometric pattern recognition algorithms. Sequencing is essential for many tasks, including as feature extraction, model training, and preprocessing. Eliminating background noise and obtaining dense vertical edges are part of the preprocessing procedures. Facial feature extraction will be employed to extract features after feature extraction. Use attributes cautiously when training a Desnet121-BiLstM model. In every respect, the suggested method outperforms two state-of-the-art algorithms, Desnet121 and BiLstM. An accuracy rating of 97.19% was indicative of a considerable improvement in the figures. © 2024 IEEE.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

Enhancing student Placement Predictions with a Trans-CLstM Based Recommendation System 1

Enhancing Student Placement Predictions with a Trans-CLSTM B...

引用

1st IEEE international conference on Electronics, Computing, Communication and control Technology, ICECCC 2024

作者： Nishant, Neerav Magadum, Alkawati Pandey, Vivekanand Suganthi, D. Unni, Manu Vasudevan Anusuya, S. Babu Banarasi Das University Department of CSE School of Engineering Lucknow India MIT-ADT University College of Management Department of MCA Maharashtra Pune India Amity University Department of Management Pune India Saveetha College of Liberal Arts and Sciences SIMATS Department of Computational Intelligence Chennai India St. Claret College Department of Management Bangalore India K. Ramakrishnan College of Engineering Department of ECE Trichy Samayapuram India

ISBN: (纸本)9798350371802

Enhancing students' employability poses a major hurdle for educational institutions in the present day, considering the intricate nature of educational entities. Institutions are finding ways to leverage technology in order to improve their administrative processes and decision-making capabilities. Providing comprehensive insights into educational processes and entities through advanced data analytics is crucial for a successful strategy. This study emphasises three crucial components: data preprocessing, feature selection, and model training. Data preprocessing is crucial for ensuring that the dataset is well-prepared for analysis. Various feature selection techniques are used to determine the most relevant features for training purposes. The proposed Trans-CLstM models surpass traditional algorithms like LstM and CNN, showcasing substantial enhancements in accuracy, achieving an impressive accuracy rate of 98.22%. This research adds to the ongoing efforts to improve educational quality and student outcomes using data-driven approaches. © 2024 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Smart control for Solar PV-Grids to Enhance Power Quality using Deep Neuro Auto Inverter Model 1

Smart Control for Solar PV-Grids to Enhance Power Quality us...

引用

1st international conference on Innovations in Communications, Electrical and Computer engineering, ICICEC 2024

作者： Sudharani, S. Godwin Immanuel, D. Sathyabama Institute of Science and Technology Department of Electrical and Electronics Engineering Chennai India

ISBN: (数字)9798350376517

ISBN: (纸本)9798350376517

Power quality upgrade in grid-connected photovoltaic systems ensures stable and highly efficient operation of modern energy grids. Meanwhile, the high penetration of renewable energy sources brings real challenges to the maintenance of high power quality, associated with the problems of harmonics, voltage instability, and reactive power balance. In this paper, an advanced neural network-based control for the inverter is utilized to dynamically optimize inverter settings for the abatement of common power quality problems. It will adapt the model through deep learning algorithms to real-time conditions - a sophisticated approach in managing harmonic distortions, stabilizing voltage fluctuations, and optimizing reactive power. The proposed NAIC model represents a significant improvement over the traditional methods of control. Its flexibility and adaptability enhance efficiencies in power conversion and thus improve the stability of the grid. The NAIC learns from real-time data, adapting control parameters continually during the process, which enhances the performance in solar power systems for assured reliability and efficiency of operation of the power grid. This paper presents effectiveness of neural network approaches for power quality management, and describes future directions towards more research and developments in this crucial area of renewable energy integration. © 2024 IEEE.

关键词： Photovoltaic systems Reactive power Renewable energy sources Adaptation models Power quality Power system stability Inverters Real-time systems stability analysis Research and development

来源：评论

学校读者我要写书评

暂无评论

An Automatic ATM Card Fraud Detection Using advanced Security Model Based on AOA-CNN-XGBoost Approach 1

An Automatic ATM Card Fraud Detection Using Advanced Securit...

引用

1st IEEE international conference on Electronics, Computing, Communication and control Technology, ICECCC 2024

作者： Porkodi, T. Rajkumar, R. Sathiya, R. Senthil Raja, M. B. S. Abdur Rahman Crescent Institute of Science & Technology Department of Commerce Tamil Nadu Chennai India Annamalai University Chidambaram Department of Commerce Tamil Nadu Cuddalore India St. Ann's College of Arts & Science Annamalai University Department of Computer Science Tamil Nadu Tindivanam India College of Engineering & Technology SRMIST Kattankulathur Department of Computing Technologies Tamil Nadu Chennai India

ISBN: (纸本)9798350371802

The implications of financial fraud are becoming more significant as the risk of it grows. For two main reasons, data mining for the purpose of detecting ATM card fraud is quite difficult. First, datasets about ATM card fraud frequently display significant bias. Second, what constitutes legitimate and fraudulent behavior is defined differently every time. The variables chosen and the sample methods used have a direct bearing on how well ATM card fraud detection algorithms work. Card fraud at ATMs is a major threat to the security of online payment systems and banking. Model training, feature reduction, preprocessing, and procedure selection must all be part of a systematic approach. The importance of preprocessing in avoiding inaccurate model output and keeping data quality high cannot be overstated. As part of the preprocessing step known as feature reduction, correlation-based measures are used to examine feature correlation. After that, the model is trained using AOA-CNN-XGBoost, which produces remarkable outcomes with a 97.13% accuracy rate. © 2024 IEEE.

关键词： Data mining

来源：评论

学校读者我要写书评

暂无评论

Recent Advances in Hybrid Energy storage Systems for Remote standalone Renewable Energy Plant 1

Recent Advances in Hybrid Energy Storage Systems for Remote ...

引用

1st international conference on engineering and advanced Technology, ICEEAT 2023

作者： Omrane, Bouketir Abderrahim, Saib Alaeddine, Fenni Ferhat Abbas University Setif1 Mechatronics Laboratory Department of Electrical Engineering Setif Algeria

ISBN: (纸本)9798350383485

The increasing demand for reliable and sustainable energy sources has led to significant advancements in the field of hybrid energy storage systems (HESS) for remote stand-alone power plants. These power plants, located in off-grid and isolated areas, face unique challenges due to their distance from conventional energy infrastructure. As a result, researchers and engineers have been actively pursuing innovative solutions that combine multiple energy storage technologies to ensure continuous and efficient power supply. This abstract highlights the recent progress in the development of hybrid energy storage systems tailored for remote stand-alone power plants. The integration of diverse energy storage technologies, such as batteries, supercapacitors, and flywheels, has emerged as a promising strategy for addressing the intermittency of renewable energy sources in remote locations. Recent advancements have focused on optimizing the operation and control strategies of HESS to maximize energy utilization, minimize storage losses, and extend system lifespan. advanced control algorithms, including model predictive control (MPC) and artificial intelligence (AI) algorithms, have been applied to manage the charge and discharge cycles of different storage components effectively. © 2023 IEEE.

关键词： Model predictive control

来源：评论

学校读者我要写书评

暂无评论

Ethical and Practical Implications of Implementing Facial Recognition Technology for Attendance control in Educational Institutions and Businesses 1

Ethical and Practical Implications of Implementing Facial Re...

引用

1st IEEE international conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Kurup, Ravindra Muzalda, Devendra Sharma, Vinod Hudda, Yashika Singh, Vijay Vir Princy, Benila Madhav University Dept. of Humanities and S.Science Pindwara India SLP College Dept of CSE Gwalior India Chandigarh University Dept of Computer Science Engineering Chandigarh India Lingayas Vidyapeeth Dept. of Mathematics Faridabad India Meenakshi A.H.E.R Dept. of English Chennai India

ISBN: (纸本)9798350356816

Facial recognition technology has garnered significant attention recently as a potential solution for attendance management in educational institutions and companies. This study proposes a facial recognition attendance system designed to address limitations of existing systems and navigate the ethical and legal considerations associated with the technology. To ensure accuracy, security, and user acceptance, the proposed system integrates advanced facial recognition algorithms, strict data protection protocols, and intuitive interfaces. The methodology encompasses a thorough literature review, primary data collection through surveys and interviews, system design, testing, and data analysis to evaluate the feasibility, efficacy, and ethical implications of deploying facial recognition for attendance tracking. The experimental setup includes cameras, laptops, servers, facial recognition algorithms, attendance management software, and a diverse collection of facial images. Analysis of the collected data aims to assess the system's accuracy and effectiveness. The study's findings will offer insights into the potential benefits and challenges of adopting facial recognition technology for attendance management in educational and corporate settings, along with recommendations for future research and implementation. © 2024 IEEE.

关键词： Accuracy Attendance Management Data Analysis Diverse Facial Image Facial Recognition

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Based Real-Time Hand Landmark Recognition with MediaPipe for R12 Robot control 1

Deep Learning-Based Real-Time Hand Landmark Recognition with...

引用

1st international conference on engineering and advanced Technology, ICEEAT 2023

作者： Bensaadallah, Mohamed Ghoggali, Noureddine Saidi, Lamir Ghoggali, Walid University of Batna 2 Dept. of Electronics Batna Algeria University of Batna 2 Laaas Batna Algeria Dept. Kynesim Ltd CambridgeCB1 7EB United Kingdom

ISBN: (纸本)9798350383485

In the evolving world of robotics, the way humans and robots interact plays a crucial role in the overall system performance and user experience. Traditionally, robotic control for accomplishing tasks have been dominated by programming languages like ROBOFORTH or touchpad interfaces. However, these methods often create barriers to user interaction. This study explores the potential of hand gesture recognition, specifically focusing on the deep-learning MediaPipe library's real-time hand-landmark detection capabilities. We present a system that combines MediaPipes abilities with controlling the st Robotics R12 robot, allowing real-time hand gestures to be translated into robotic drawing actions and tasks. This integration offers a natural and interactive communication medium that could revolutionize how humans carry out tasks with robots. By leveraging MediaPipes computer vision and deep learning techniques, we successfully controlled the R12 robot through gesture-based interactions. The system effectively translated hand gestures into robotic drawing functions and specific tasks such as object relocation. However, future improvements should concentrate on enhancing precision, reevaluating reliance on ROBOFORTH and exploring MATLAB Simulink's potential for advanced gesture-based control algorithms. © 2023 IEEE.

关键词： MATLAB

来源：评论

学校读者我要写书评

暂无评论

Volt/Var control in Distribution Network: An Overview 1

Volt/Var Control in Distribution Network: An Overview

引用

1st international conference on Sustainable Technology for Power and Energy Systems, stPES 2022

作者： Jaiswal, Aman Saxena, Dipti Malaviya National Institute of Technology Department of Electrical Engineering Jaipur India

ISBN: (纸本)9781665459150

Integration of renewable energy sources and load create challenges of economical operation of the grid at the same time power quality issues also arises. To minimize the challenges of power quality disturbances numerous research has been conducted. However very little focus is given to voltage deviation and reactive power control. Both the issue of voltage and reactive power are interdependent need to be address by a common tool. The volt-var control(VVC) concept has been adopted in existing literature which has been thoroughly addressed in this review paper. The principal goal of this study is to examine and compare existing and new approaches and algorithms for advanced VVC applications. Further, it gives the reader a thorough overview of the optimization techniques as well as objective in terms of reduction of loss, voltage deviation, energy demand reduction and minimum control variable operation. © 2022 IEEE.

关键词： Reactive power

来源：评论

学校读者我要写书评

暂无评论

Rethinking Distribution Alignment for Inter-class Fairness 1

引用

1st international conference on Artificial Intelligence Security and Privacy, AIS and P 2023

作者： Ye, Jinhuang Wu, Jiawei Li, Zuoyong Zheng, Xianghan College of Computer and Big Data Fuzhou University Fuzhou350108 China School of Intelligent Systems Engineering Sun Yat-sen University Shenzhen518107 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China

ISBN: (数字)9789819997886

ISBN: (纸本)9789819997879

Semi-supervised learning (SSL) is a successful paradigm that can use unlabelled data to alleviate the labelling cost problem in supervised learning. However, the excellent performance brought by SSL does not transfer well to the task of class imbalance. The reason is that the class bias of pseudo-labelling further misleads the decision boundary. To solve this problem, we propose a new plug-and-play approach to handle the class imbalance problem based on a theoretical extension and analysis of distribution alignment. The method, called Basis Transformation Based Distribution Alignment (BTDA), efficiently aligns class distributions while taking into account inter-class *** implements the basis transformation through a learnable transfer matrix, thereby reducing the performance loss caused by pseudo-labelling biases. Extensive experiments show that our proposed BTDA approach can significantly improve performance in class imbalance tasks in terms of both accuracy and recall metrics when integrated with advanced SSL algorithms. Although the idea of BTDA is not complex, it can show advanced performance on datasets such as CIFAR and SVHN. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Image classification

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15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：