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

891 篇 会议
6 册 图书
5 篇 期刊文献

馆藏范围

902 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

611 篇 工学
- 514 篇 计算机科学与技术...
- 320 篇 软件工程
- 102 篇 信息与通信工程
- 94 篇 电气工程
- 78 篇 生物工程
- 72 篇 控制科学与工程
- 47 篇 环境科学与工程（可...
- 35 篇 机械工程
- 35 篇 安全科学与工程
- 30 篇 交通运输工程
- 29 篇 生物医学工程（可授...
- 28 篇 动力工程及工程热...
- 24 篇 建筑学
- 23 篇 光学工程
- 18 篇 电子科学与技术（可...
186 篇 理学
- 87 篇 数学
- 81 篇 生物学
- 30 篇 统计学（可授理学、...
- 29 篇 物理学
- 22 篇 系统科学
132 篇 管理学
- 99 篇 管理科学与工程(可...
- 50 篇 图书情报与档案管...
- 48 篇 工商管理
112 篇 教育学
- 111 篇 教育学
49 篇 法学
- 40 篇 社会学
36 篇 医学
- 35 篇 临床医学
- 34 篇 基础医学(可授医学...
- 25 篇 公共卫生与预防医...
21 篇 经济学
- 21 篇 应用经济学
19 篇 农学
- 19 篇 作物学
6 篇 军事学
4 篇 文学

主题

82 篇 machine learning
60 篇 deep learning
43 篇 internet of thin...
40 篇 accuracy
38 篇 ecosystems
25 篇 predictive model...
23 篇 reinforcement le...
23 篇 training
23 篇 convolutional ne...
19 篇 real-time system...
19 篇 feature extracti...
19 篇 security
19 篇 artificial intel...
19 篇 technological in...
18 篇 big data
17 篇 computational mo...
17 篇 students
17 篇 machine learning...
16 篇 sustainable deve...
16 篇 e-learning

机构

11 篇 chitkara centre ...
9 篇 department of in...
8 篇 chitkara univers...
8 篇 aslerd rome
7 篇 chitkara univers...
6 篇 centre of resear...
5 篇 department of co...
4 篇 texas a&m univer...
4 篇 czech tech univ ...
4 篇 bina nusantara u...
4 篇 lloyd institute ...
4 篇 the islamic univ...
4 篇 univ politehn bu...
4 篇 acad romanian sc...
4 篇 lloyd law colleg...
4 篇 univ innsbruck i...
3 篇 yunnan key labor...
3 篇 kkr and ksr inst...
3 篇 vishwakarma inst...
3 篇 universidad tecn...

作者

7 篇 giovannella carl...
6 篇 urban josef
5 篇 dascalu mihai
4 篇 bakken jeffrey p...
4 篇 uskov vladimir l...
4 篇 rachakonda rama
3 篇 heinemann collee...
3 篇 maranan ramya
3 篇 p. william
3 篇 refaat shady s.
3 篇 kaliszyk cezary
3 篇 olsak miroslav
3 篇 setiawan karli e...
3 篇 santos fernando ...
3 篇 leoste janika
3 篇 trausan-matu ste...
2 篇 m. vigenesh
2 篇 zhao huijuan
2 篇 toma irina
2 篇 a l n rao

语言

836 篇 英文
64 篇 其他
5 篇 中文
1 篇 法文

检索条件"任意字段=4th International Conference on Smart Learning Ecosystems and Regional Development"

共 902 条记录，以下是161-170 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：

Towards Eco-Friendly Marine Monitoring: the development and Environmental Impact Assessment of Autonomous smart Buoys 4th

Towards Eco-Friendly Marine Monitoring: The Development and ...

引用

4th international conference of the Italian Association of Design Methods and Tools for Industrial Engineering

作者： Salmeri, Fabio Barbieri, Loris Cucinotta, Filippo Raffaele, Marcello Univ Messina Dept Engn Messina Italy Univ Calabria Dept Mech Energy & Management Engn DIMEG Arcavacata Di Rende CS Italy

ISBN: (纸本)9783031765964;9783031765971

the article discusses the environmental impacts of deploying innovative, autonomous smart buoys for marine monitoring. these buoys, notable for their compact size and lack of traditional mooring systems, are designed to minimize ecological footprints within marine ecosystems. Equipped with advanced propulsion systems, they can autonomously navigate and maintain stability in challenging sea conditions, making them ideal for monitoring coastal areas with heavy anthropogenic influence. the research introduces a new buoy design paradigm aimed at reducing environmental impact, incorporating essential sensors for monitoring and collecting water samples. A comprehensive life cycle assessment (LCA) was conducted using the Open LCA software and Ecoinvent database, adhering to ISO 14044 standards. this 'cradle-to-gate' assessment evaluates the production of the buoys, applying the ILCD 2018 method to assess a wide range of eco-sustainability indicators including global warming potential, human toxicity, and more. Following the assessment, the buoys were redesigned with a resulting reduction in emissions. the findings from the LCA are instrumental in optimizing the buoy's design, enhancing efficiency, and reducing environmental impacts.

关键词： Life Cycle Assessment smart Buoy Technology Marine Environmental Monitoring Sustainable Marine Technology Design for X

来源：评论

学校读者我要写书评

暂无评论

Predicting Urban Traffic Flow Based on Deep Meta-learning 24

Predicting Urban Traffic Flow Based on Deep Meta-learning

引用

4th international conference on Artificial Intelligence, Big Data and Algorithms, CAIBDA 2024

作者： Zhu, Wenyan Kong, Hoiio Cai, Wenzheng Zhu, Wenhao Faculty of Data Science City University of Macau China Department of Academic Affairs Guangdong University of Science & Technology Dongguan Guangdong China Co. Ltd Dongguan Guangdong China

ISBN: (纸本)9798400710247

this paper aims to explore the application of deep meta-learning in urban traffic flow prediction, analyzing its advantages over traditional methods and the challenges it faces. Firstly, we introduce the background and importance of urban traffic flow prediction, along with the current application of deep learning technologies in this field. Subsequently, the paper elaborates on the theoretical foundations and key techniques of deep meta-learning, including the design of meta-models, training strategies, and feature integration mechanisms. Additionally, through experimental comparative analysis, we demonstrate the performance of deep meta-models in traffic flow prediction tasks and discuss their potential and limitations in practical applications. Finally, the paper summarizes research findings and proposes future research directions, aiming to provide more efficient and accurate prediction tools for urban traffic management and to promote the development of smart cities. through in-depth research, we seek to offer new perspectives and solutions to the field of urban traffic flow prediction, contributing to the advancement of intelligent transportation systems. © 2024 Copyright held by the owner/author(s).

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

Building a Dashboard Farm by Simulation with Node-Red 18

Building a Dashboard Farm by Simulation with Node-Red

引用

18th international Joint Symposium on Artificial Intelligence and Natural Language Processing (ISAI-NLP) / 4th international conference on Artificial Intelligence and Internet of things (AIoT)

作者： Silawarawet, Kanchana Phurat, Tawan Thammasat Univ Dept Elect & Comp Engn Fac Engn Bangkok Pathumthani Thailand Siam Univ Fac Engn Dept Comp Engn Bangkok Thailand

ISBN: (纸本)9798350371215

the creation of a dashboard for managing smart agricultural systems necessitates installing numerous devices in the field for comprehensive testing. this allows a thorough evaluation of the dashboard's effectiveness across varied scenarios. Testing aims to determine how the system responds to dynamic environmental factors like temperature, humidity, and light, which significantly impact device performance. However, natural environmental complexities, characterized by temporal and spatial heterogeneity, make replicating conditions challenging. this research proposes using virtual nodes as digital counterparts to physical devices. these nodes emulate device functionality in a controlled manner, overcoming logistical challenges of physical deployment. Developers can simulate diverse scenarios, providing insights into device responses under varying environmental conditions. this research introduces a novel approach for evaluating smart farm dashboards, highlighting the potential of virtual nodes as tools for system development within intricate agricultural ecosystems in order to evaluate, compare the behavior of the smart farm system with simulation node and actual node, and to ensure that the smart farm system works as intended without interference by farmer. this contributes to the discourse on technology integration in agriculture, enhancing efficiency and sustainability in farming practices.

关键词： smart farm control Node-RED dashboard

来源：评论

学校读者我要写书评

暂无评论

Load Aggregation Quotient Incentive Strategy Based on Multi Agent Reinforcement learning 4

Load Aggregation Quotient Incentive Strategy Based on Multi ...

引用

4th international conference on New Energy and Power Engineering, ICNEPE 2024

作者： Kang, Yiqun Xiong, Haozhe Liu, Dan Feng, Wanli Li, Zhe Ao, Yuqi State Grid Hubei Electric Power Co. Ltd. Electric Power Research Institute Wuhan China

ISBN: (纸本)9798331516086

With the development of modern and advanced information and communication technologies in smart grid systems, demand response (DR) has become an effective way to improve the reliability of the grid system and reduce energy costs by adjusting the flexible load on the demand side, which can quickly solve the imbalance between supply and demand. Firstly, based on the uncertainty of user participation in demand response, the incentive method of dynamic pricing is used to establish the demand response model of LA and the user side, secondly, reinforcement learning (RL) is used to explain the decision-making problem between LA and users, and the dynamic pricing problem is expressed as a discrete finite Markov decision process (MDP), and finally, the multi-agent deep deterministic policy gradient method is used Gradient) to solve the decision problem. Using the MADDPG algorithm, considering the profits of LA and users, the best incentive rate for different users is obtained. the simulation results show that LA can learn its strategy without a priori information of the microgrid, adaptively formulate the optimal incentive for each user, improve the profit of LA and users, reduce energy costs, and balance the energy supply and demand of the power market. © 2024 IEEE.

关键词： Demand response

来源：评论

学校读者我要写书评

暂无评论

Deep learning-Based Control Model for Electronic Evidence Access Rights 4

Deep Learning-Based Control Model for Electronic Evidence Ac...

引用

4th international conference on Information Science, Parallel and Distributed Systems, ISPDS 2023

作者： Chen, Peng Li, Yongliang Gao, Xianzhou State Grid Ningxia Electric Power Co.Ltd. Ningxia750001 China State Grid Ningxia Electric Power Co.Ltd. Electric Power Research Institute Ningxia750002 China State Grid Smart Grid Research Institute Co. Ltd. Nanjing210003 China State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology Nanjing210003 China

ISBN: (纸本)9798350337181

With the rapid development of digitalization and intelligence in smart grids, how to identify untrusted users in the electric power system and implement user access control based on electronic evidence has become an important research topic. A credible assessment needs to be made on the subject users accessing electronic evidence. In this paper, we propose a deep learning-based user multi-dimensional attribute feature extraction access control model, which considers multi-dimensional attribute features such as user identity, behaviour, and device information, and determines whether the user is a legitimate access user by using CNN-Transformer deep learning framework to extract user features and determine their trust value. through simulation experiments, it is proved that the access permission control model proposed in this paper has high accuracy and reliability and can meet the access requirements of different electronic evidence users. © 2023 IEEE.

关键词： smart power grids

来源：评论

学校读者我要写书评

暂无评论

development of Residential Load Simulator for Advanced Residential Energy Management 4

Development of Residential Load Simulator for Advanced Resid...

引用

4th international conference on smart Grid and Renewable Energy, SGRE 2024

作者： Amer, Aya Bayhan, Sertac Ehsani, Mark Massoud, Ahmed Texas A&M University College Station Electrical and Computer Engineering Department United States Hamad Bin Khalifa University Qatar Environment and Energy Research Institute Doha Qatar Qatar University Electrical Engineering Department Doha Qatar

ISBN: (纸本)9798350306262

In an era where residential energy consumption and management have become pivotal components of modern power grids, it is essential to develop tools that enable a deeper understanding of household energy dynamics. this paper responds to this point by introducing a Residential Load Simulator (RLS) for dynamic load modeling. the simulator features unique aspects of the user interface, different types of household appliances, and incorporates the modeling of renewable energy resources. It can be customized to different types of residential setups or geographic locations. this includes various household sizes, climatic conditions, or energy consumption patterns. Also, it can be used as an educational tool for students, homeowners, or energy professionals, offering a comprehensive platform to test and refine home energy management strategies. these features make it an excellent resource for both academic and practical learning, helping to bridge the gap between theoretical knowledge and real-world applications. © 2024 IEEE.

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

A Way of Making smart Health through Collaborating Machine learning with the Bibliometrics 4

A Way of Making Smart Health Through Collaborating Machine L...

引用

4th IEEE international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2024

作者： Vignesh, T. Sruthi, P.S. Mohanraj, T. Kumar, Gaurav Varkale, Akshay Sheela, M.Sahaya Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering TN India Nehru Institute of Technology Department of Computer Science and Business System Tamil Nadu T.M. Palayam India Karpagam Academy of Higher Education Department of Computer Science Engineering India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh India M.P Bhopal India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350360165

It datasets are widely utilized, shared, and repurposed without providing enough context for understanding the decision-making processes that led to their creation. It is necessary to modify system creation and use procedures to handle the concrete effects of how knowledge for model building is envisioned and used in real-world applications as AI systems assume more and more important roles. Documents are created at every phase of the data generation lifecycle to improve communication, aid in decision-making, and highlight the need of careful data work. By putting out this paradigm, we want to shed light on the choices and duties that are often disregarded while creating datasets, which is a crucial first step in bridging the duty of care gap in AI. this framework provides an essential and important resource for guaranteeing ethical AI activities, and it is in line with current developments in auditing procedures. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Transfer learning based architecture for urban transportation Big data fusion 22

Transfer Learning based architecture for urban transportatio...

引用

14th international conference on Management of Digital ecosystems (MEDES)

作者： Ghodhbani, Salah Elkosantini, Sabeur Suh, Wonho Lee, Mark Univ Tunis SMART LA ISG Tunis Tunis Tunisia Univ Carthage FSEG Nabeul Tunis Tunisia Hanyang Univ ERICA Campus Ansan South Korea United Arab Emirates Univ Abu Dhabi U Arab Emirates

ISBN: (纸本)9781450392198

Recently, intelligent transportation system (ITS) is considered as one of the most important issues in smart city applications. Its supports urban and regional development and promotes economic growth, social development, and enhances human well-being. ITS integrates new technologies of information and communication including sensors, social media IoT devices which can generate a massive amount of heterogeneous and multimodal data known as big data term. In this context, Data Fusion techniques (DF) seem promising and have emerged from transportation applications and hold a promising opportunities to deal with imperfect raw data for capturing reliable, valuable and accurate information. Literature. In literature many DF techniques based on machine learning remarkably renovates fusion techniques by offering the strong ability of computing and predicting. In this paper, we propose new Hybrid method based on TL (transfer learning) combine tow pertained DL models such as irregular CNN [1], and bi-directional LSTM [2] models to fuse multimodal and spatial temporal data. the propose method use CBOA algorithm for feature selection in to order to provide effective exploration of significant features with faster convergence. the proposed model demonstrated its effective results on the applied dataset by offering good results and outcome over traditional methods.

关键词： Big Data Data fusion urban transportation CBOA Transfer learning Irregular CNN Bi-directional LSTM

来源：评论

学校读者我要写书评

暂无评论

Arduino-Based Air Quality Monitoring Robot With ML Analysis 4

Arduino-Based Air Quality Monitoring Robot With ML Analysis

引用

4th international conference on Pervasive Computing and Social Networking (ICPCSN)

作者： Sivaramakrishnan, S. Janga, Santosh Reddy Yuktha, S. Darshini, R. Monisha, R. New Horizon Coll Engn Informat Sci & Engn Bangalore Karnataka India

ISBN: (纸本)9798350386356;9798350386349

As everyone is aware, many dangerous gasses are emitted from automobiles and industry, which can lead to a range of health issues such as lung cancer, asthma, and a range of heart-related complications, or even lead to premature death if the ambient pollution is severe. the consequences of ambient pollution such as acid rain, global warming, and negative effects on agriculture and water quality, emphasize the vital need of ongoing air quality monitoring. As a result, a smart monitoring robot is required to check the air quality. this paper proposes the development of an Air Quality Monitoring Robot capable of efficiently monitoring real-time air conditions via the thing Speak IoT website. the key components of the device include an Arduino Uno, Motor Driver, DC motors, MQ9 and MQ135 gas sensors (for the detection of gases like carbon dioxide, methane, hydrogen, etc.), temperature sensor, LCD display, and an ESP8266 Wi-Fi module. Additionally, an ultrasonic sensor is incorporated into the design. the planned system is created to provide a user-friendly mobile application and web-based interface. the monitoring results are accessible in real-time through a web application, which connects to a Wi-Fi network. the robot, equipped with these specified sensors and modules, plays a critical function in data collection and environmental monitoring. Additionally, machine learning algorithms are used to identify patterns in the data and predict changes in air quality, allowing users to take preventive actions before air quality deteriorates. Another area of future work could be to improve the user interface and data visualization of the system, making it more accessible and easier to use for non-experts. Overall, continued development and optimization of the system can help to increase its effectiveness and applicability in a variety of settings, from indoor air quality monitoring in homes and offices to outdoor pollution monitoring in urban environments.

关键词： air quality monitoring Iot Robot Arduino Uno MQ9 MQ135 ultra sonic sensor machine learning

来源：评论

学校读者我要写书评

暂无评论

Ensemble Approach for Early Prediction of Malnutrition Level of Children: A Case Study on Children Under Five Years Old 4

Ensemble Approach for Early Prediction of Malnutrition Level...

引用

4th international conference on Advanced Research in Computing, ICARC 2024

作者： Nirmani, H.M.C. Kudagamage, U.P. Sabaragamuwa University of Sri Lanka Department of Computing and Information Systems Belihuloya Sri Lanka

ISBN: (纸本)9798350384864

Malnutrition refers to inadequate nutritional intake, nutrient imbalances or impaired nutrient utilization which is a global health issue that has a significant effect on children, leading to short-term and long-term consequences for their growth, development and overall well-being. the critical period for a child's growth and development is 1 to 60 months. the early identification of a child's malnutrition status is a strong foundation for lifelong health and well-being. therefore, the objective here is to develop a model for early detection, and prediction of malnutrition in children. this study draws on a sample of 574 children under the age of five years in the Lunugala area, who were chosen randomly to be involved in the development of a predictive model for malnutrition using ensemble learning techniques. After pre-processing the collected sample, the dataset was partitioned into 70% of training set and 30% of testing set. Nine Machine learning algorithms, namely Support Vector Machine (SVM), Decision Tree (DT), Guassian Naïve Bayes (GNB), Bernoulli Naïve Bayes (BNB), Complement Naïve Bayes (CNB), Logistic Regression (LR), Random Forest (RF), AdaBoost and Extreme Gradient Boosting (XGBoost) were initially used. And the evaluation metrics including accuracy, precision, recall and F-measure were utilized to access the performance of these individual algorithms. After comparing the nine base learners with each other based on accuracy, the three best performing Machine learning algorithms were combined and integrated into an ensemble model using techniques such as Soft Voting Classifier, Hard Voting Classifier and Stacking Classifier. the evaluation of these ensemble models, also based on accuracy, precision, recall and F-measure revealed that the Stacking Classifier achieved the highest accuracy of 93%. Consequently, the study concludes that the ensemble learning technique is well-suited for better prediction of malnutrition status. © 2024 IEEE.

关键词： learning systems

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91页 << < 13 14 15 16 17 18 19 20 21 22 > >>

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：