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

6,535 篇 会议
3,753 篇 期刊文献
24 册 图书

馆藏范围

10,312 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

6,193 篇 工学
- 4,381 篇 计算机科学与技术...
- 3,759 篇 软件工程
- 1,405 篇 控制科学与工程
- 1,328 篇 信息与通信工程
- 862 篇 生物工程
- 816 篇 电气工程
- 659 篇 生物医学工程（可授...
- 634 篇 机械工程
- 596 篇 光学工程
- 485 篇 电子科学与技术（可...
- 367 篇 仪器科学与技术
- 332 篇 网络空间安全
- 292 篇 交通运输工程
- 289 篇 化学工程与技术
- 286 篇 动力工程及工程热...
- 281 篇 安全科学与工程
3,365 篇 理学
- 1,623 篇 数学
- 1,003 篇 生物学
- 849 篇 物理学
- 625 篇 统计学（可授理学、...
- 401 篇 系统科学
- 380 篇 化学
1,827 篇 管理学
- 1,162 篇 管理科学与工程(可...
- 747 篇 图书情报与档案管...
- 474 篇 工商管理
695 篇 医学
- 566 篇 临床医学
- 458 篇 基础医学(可授医学...
- 309 篇 公共卫生与预防医...
- 270 篇 药学(可授医学、理...
285 篇 法学
- 251 篇 社会学
216 篇 经济学
167 篇 农学
90 篇 教育学
32 篇 文学
24 篇 军事学
7 篇 艺术学
1 篇 历史学

主题

565 篇 accuracy
461 篇 deep learning
336 篇 feature extracti...
323 篇 real-time system...
310 篇 machine learning
284 篇 training
234 篇 predictive model...
228 篇 computational mo...
209 篇 convolutional ne...
187 篇 semantics
171 篇 support vector m...
162 篇 optimization
152 篇 reinforcement le...
144 篇 data models
141 篇 artificial intel...
132 篇 internet of thin...
132 篇 neural networks
118 篇 object detection
118 篇 visualization
108 篇 image segmentati...

机构

808 篇 school of artifi...
527 篇 school of artifi...
135 篇 state key labora...
134 篇 institute of aut...
123 篇 huazhong univers...
118 篇 institute of art...
107 篇 faculty of infor...
96 篇 school of artifi...
93 篇 university of sc...
89 篇 yunnan key labor...
81 篇 cas center for e...
80 篇 national key lab...
80 篇 institute of art...
75 篇 national laborat...
74 篇 school of automa...
72 篇 university of ch...
64 篇 department of ar...
59 篇 vishwakarma inst...
53 篇 centre of interd...
53 篇 ieee

作者

85 篇 ashwini kodipall...
61 篇 tao jianhua
48 篇 hai-tao zhang
47 篇 zeng zhigang
38 篇 yi jiangyan
37 篇 sang nong
35 篇 wen zhengqi
33 篇 zhiguo cao
33 篇 jianhua tao
33 篇 liu yang
30 篇 wei he
29 篇 li yang
29 篇 lu hao
27 篇 huang jian
27 篇 kodipalli ashwin...
26 篇 liu lei
25 篇 zhang hai-tao
24 篇 ye yuan
24 篇 yu kang
24 篇 fu ruibo

语言

6,848 篇 英文
3,390 篇 其他
115 篇 中文
3 篇 斯洛文尼亚文
2 篇 德文
2 篇 法文

检索条件"机构=Artificial Intelligence and Data Science in Automation Technology"

共 10312 条记录，以下是91-100 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：

Short-term load forecasting based on improved optimization algorithms 9

Short-term load forecasting based on improved optimization a...

引用

9th International Symposium on Advances in Electrical, Electronics, and Computer Engineering, ISAEECE 2024

作者： Zhang, Jiaan Ning, Ruanhao School of Artificial Intelligence and Data Science Hebei University of Technology TianJing China

ISBN: (纸本)9781510683303

Accurate predictions of electricity load are crucial for the safe and stable operation, as well as the economic performance, of power systems. To overcome the inadequacy of feature selection and the difficulty in tuning model hyperparameters in traditional load forecasting models — issues that may lead the predictive model into local optima — this paper proposes a short-term electricity load forecasting method based on ***, the eXtreme Gradient Boosting (XGBoost) tree model is employed for feature selection. Subsequently, the Improved artificial Rabbits Optimization (IARO) algorithm is enhanced using tent chaotic mapping, elite reverse learning strategy, and hybrid reverse learning strategy. The improved IARO algorithm is then utilized to tune the hyperparameters of Long Short-Term Memory (LSTM).Finally, the XGBoost-IARO-LSTM combined forecasting model is established to achieve accurate short-term load predictions. The proposed method is validated using real electricity load data from a specific region in northern China. The results indicate that the proposed approach exhibits faster parameter optimization speed and superior prediction performance. © 2024 SPIE.

关键词： Photons

来源：评论

学校读者我要写书评

暂无评论

Detecting and Responding to Cloud Privilege Escalation Attacks Using Machine Learning 6

Detecting and Responding to Cloud Privilege Escalation Attac...

引用

6th International Conference on Cybernetics, Cognition and Machine Learning Applications, ICCCMLA 2024

作者： Tabassum, Sheema Ramana, K. Chaitanya Bharathi Institute of Technology Artificial Intelligence and Data Science Hyderabad India

ISBN: (纸本)9798331505790

The field of cloud computing has created as an extremely productive region for complete innovative work, drawing in critical consideration from proficient organizations and organizations the same. The quick multiplication of PCs, information organizations, and other basic applications has brought about a more prominent accentuation on network safety. This exploration utilizes state of the art ML procedures to distinguish and forestall honor acceleration dangers, consequently supporting cloud security. Strong insurances are fundamental since utilizing cloud administrations builds the risk of these attacks. To work on generally speaking security, the review targets shortcomings in representative access freedoms in cloud settings utilizing ML methods like LightGBM, RF, AdaBoost, and XGBoost. This empowers ongoing discovery and relief of honor acceleration endeavors while adjusting quickly to evolving dangers. Moreover, a 'soft' Voting Classifier that joins forecasts from RF, DT, and SVM supports framework execution considerably further. The blend of a simple to-utilize Flask framework with SQLite gives secure information exchange and sign-in usefulness while enhancing client testing for true arrangement. This far reaching technique not just further develops client and business information security and encourages distributed computing trust, however it likewise helps cloud specialist co-ops' and associations' trust in their ability to keep a protected web-based climate. Among the proposed calculations, the Voting Classifier scored the best execution accuracy of 96.45 %, while LightGBM accomplished 94 %. The leftover accuracy scores are as per the following: RF (95 %), AdaBoost (95 %), and XGBoost (9 4 %). © 2024 IEEE.

关键词： Cloud security

来源：评论

学校读者我要写书评

暂无评论

Catalyst: Transition from Web2 to Web3

Catalyst: Transition from Web2 to Web3

引用

2024 International Conference on artificial intelligence and Quantum Computation-Based Sensor Applications, ICAIQSA 2024

作者： Savale, Vaishali Pawar, Dhiraj Shethji, Parth Patil, Mayur Vishwakarma Institute of Technology Department of Artificial Intelligence and Data Science Pune India

ISBN: (纸本)9798331517953

The internet is evolving from Web2's centralized model, dominated by a few tech giants, to Web3's decentralized future. Web3 dismantles walled gardens, distributing data and applications across a peer-to-peer network. Imagine information not on a single server, but replicated across countless computers. This fosters transparency and eliminates censorship. Users, not platforms, own their data. Web3 empowers creators - artists can issue tokens tied to their work, allowing fans to directly support them and even own a piece. Tokens act as the fuel for a new economy, rewarding users for contributing to projects and fostering a more collaborative online experience. This shift towards decentralization has the potential to create a more equitable and user-centric internet, one where power lies not with corporations, but with the users themselves. © 2024 IEEE.

关键词： Blockchain Claude Gemini Hard hat Large Language Model Solidity

来源：评论

学校读者我要写书评

暂无评论

Innovative Approaches to Cardiovascular Disease: Machine Learning Predictions Unveiled & Interpretation using LIME & SHAP 2

Innovative Approaches to Cardiovascular Disease: Machine Lea...

引用

2nd IEEE International Conference on Integrated intelligence and Communication Systems, ICIICS 2024

作者： Reddy, Vonteddu Adharsh Dilish, M. Kodipalli, Ashwini Rao, Trupti Rohini, B.R. Gargi, N. Department of Artificial Intelligence and Data Science Global Academy of Technology Bangalore India

ISBN: (纸本)9798331504960

This study investigates how machine learning classification could revolutionize the field of cardiovascular disease prediction. By utilizing a variety of datasets that include demographic, lifestyle, and clinical information, several algorithms such as Logistic Regression, KNN, SVM, Decision Tree Classifier, GradientBoost, AdaBoost, XGBoost, Hyperparameter tuning, LIME and SHAP are used to create prediction models. The research hopes to facilitate early interventions and preventative measures by improving individualized risk assessments and their accuracy. The findings demonstrate the effectiveness of ML in predicting cardiovascular risks, indicating a paradigm change in the direction of preventive healthcare. With further development, incorporating these models into clinical practice may be able to reduce the prevalence of cardiovascular illnesses worldwide by implementing timely and focused therapies. © 2024 IEEE.

关键词： Risk assessment

来源：评论

学校读者我要写书评

暂无评论

SAR Images Change Detection Based on Maximum Classifier Difference with Multiscale Multilevel Features

SAR Images Change Detection Based on Maximum Classifier Diff...

引用

2024 China automation Congress, CAC 2024

作者： Ling, Zhiquan Yang, Dedong The School of Artificial Intelligence and Data Science Hebei University of Technology Tianjin China

ISBN: (纸本)9798350368604

Synthetic aperture radar (SAR) images can still be effective under harsh weather and lighting conditions, but the presence of scattering noise and the lack of labeled sufficient datasets have severely impacted the development of change detection (CD) methods and limited the performance of CD models. In order to solve the above problems and make full use of the existing labeled data, we propose a CD model based on the maximum classifier difference of multi-scale features. Firstly, we extract multiscale features directly from the original images and fuse them, after which the multiscale features are fed into a Siamese network for multilevel feature extraction, followed by fusion of the multilevel features for use in subsequent CD. The extracted features are then fed into the classification module and subjected to maximum classifier variance processing. While ensuring the performance of the model on the source domain dataset, the parameters of the two classifiers are updated so that the difference between their results on the target domain dataset increases, and then the parameters of the feature extractor are updated so that the difference between the results of the two classifiers on the target domain dataset decreases. Repeating the above process can achieve a reduction in the difference between the source and target domain datasets, so that the model can make full use of the labeled data and can perform well on the unlabeled data as well. We conducted comparative experiments on four publicly available SAR datasets, and the experimental results demonstrate the effectiveness and sophistication of the method. © 2024 IEEE.

关键词： Change detection

来源：评论

学校读者我要写书评

暂无评论

Credit Card Fraud Analysis Using Machine Learning 8th

Credit Card Fraud Analysis Using Machine Learning

引用

8th International Conference on Emerging Research in Computing, Information, Communication and Applications, ERCICA 2023

作者： Charitha, Sree Chowdary, Shivani Rao, Trupthi Kodipalli, Ashwini Kamal, Shoaib Rohini, B.R. Department of Artificial Intelligence and Data Science Global Academy of Technology Bangalore India

ISBN: (纸本)9789819976324

One of the important societal issues affecting the credit card business is fraud. The world has large impact on this problem. The main objectives are to first identify and categorize the different types of credit card theft before reviewing other fraud detection techniques that have been used. We are working to analyze and lesson global fraud. This paper discusses popular phrases used in credit card fraud analysis and highlights significant facts and numbers. Depending on the type of fraud that banks or credit card firms are dealing with, several precautions and processes can be created and implemented. The strategy proposed in this study is likely to be advantageous in a variety of ways, and the method presented employs machine learning methods. The reduction of credit card scam is why it is crucial to use the tactics we have discussed here. In addition, it raises ethical questions when legitimate credit card users are mistakenly labeled as fraudsters. The next step is to apply our model to determine whether or not another transaction is dishonest. Thus, it is important to treat this issue with utmost care. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Automated Medicinal Plant Identification through Image Processing and Machine Learning 8

Automated Medicinal Plant Identification through Image Proce...

引用

8th IEEE International Conference on Computing, Communication, Control and automation, ICCUBEA 2024

作者： Kadam, Yash Yache, Ajay Solunke, Pavankumar Tati, Ramakant Kachhoria, Renu Buchade, Amar Vishwakarma Institute of Information Technology Artificial Intelligence and Data Science Pune India

ISBN: (纸本)9798350391770

This research addresses the pressing challenge of accurately identifying medicinal plants in India's Ayurvedic Pharmaceutics, aiming to mitigate issues stemming from morphological variability and market adulteration. Traditional methods of plant identification are hindered by laborious processes and the potential for error, underscoring the need for an automated solution. Leveraging the power of advanced image processing and machine learning, our proposed software framework integrates the Xception model and early stopping fine-tuning to automate plant identification based on plant images. The methodology involves curating a comprehensive dataset of labelled plant images representing diverse medicinal plants, subsequently employing image preprocessing techniques to extract salient features like color, texture, and shape. The Xception model, renowned for its prowess in image recognition tasks, serves as the backbone architecture for both feature extraction and classification. To further optimize model performance and mitigate overfitting, early stopping fine-tuning techniques are applied. Through rigorous experimentation and validation, our research demonstrates the efficacy of this approach in accurately identifying medicinal plants, thereby fostering confidence and trust within the herbal medicine supply chain. By seamlessly integrating modern technological advancements with traditional botanical knowledge, our framework not only streamlines the identification process but also contributes to the sustainable utilization of herbal medicine resources. Ultimately, this research represents a pivotal step towards establishing a robust and reliable system for identifying medicinal plants, facilitating informed decision-making, and promoting the long-term viability of herbal medicine practices in India and beyond. © 2024 IEEE.

关键词： Medicinal chemistry

来源：评论

学校读者我要写书评

暂无评论

Engage Learn: An AI-Based English Proficiency Improviser 4

Engage Learn: An AI-Based English Proficiency Improviser

引用

4th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

作者： Jadhav, Balasaheb Jain, Manas Jajoo, Adhip Kadam, Devika Kadam, Harshvardhan Kakkad, Toshish Vishwakarma Institute of Technology Department of Artificial Intelligence and Data Science Pune India

ISBN: (纸本)9798331529635

In this research, the new and highly effective Web-based English learning and teaching platform called Engage Learn is introduced with the main purpose of avoiding the mistakes of the traditional models and to help users gain the ability to write and speak English more effectively. Engage Learn employs a marked-defined approach, that involves the application of several advanced technologies. Generative models including ChatGPT 3.5 turbo and Gemini 1.5 flash get enhanced presence when trained using Retrieval-Augmented Generation (RAG) technique. First, the ability for users to speak English makes for an almost informal procedure when learning since the user and the computer are communicating with one another by use of words. In addition to this, targeted feedback modules make an assessment of the user's input and give an immediate-feedback of what is required in terms of improving a user's vocabulary, grammar, and fluency. It offers another learning approach since it presents the content in a manner that is suited more to the current ability level of the user and the usage of preferred learning objectives. Engage Learn also provides flexibility of use based on learning modes as encompassed by general conversation practice, focused grammar correction and vocabulary buildup. This paper reviews the system architecture, explaining features of the different parts of the system, including the speech recognition, LLM with RAG, output analyzing, and the feedback-giving modules on grammar, vocabulary, and reading preferences. Further the paper discusses the tuning of the LLMs in a carefully selected set for language acquisition. This fine-tuning makes sure that the LLMs shall have adequate capability and knowledge required so as to get a feel about how spoken English is and about the particular feedbacks that different user may require out of them. In the last section of the abstract, the planned evaluation methods are presented with the focus on the responsibility of user te

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Design and Evaluation of an AI-Powered Conversational Agent for Personalized Mental Health Support and Intervention (MindBot) 5

Design and Evaluation of an AI-Powered Conversational Agent ...

引用

5th International Conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Kambare, Shweta M. Jain, Kriya Kale, Ishika Kumbhare, Vibhor Lohote, Sakshi Lonare, Shubham Vishwakarma Institute of Technology Department of Artificial Intelligence and Data Science Pune India

ISBN: (纸本)9798331530013

This research study describes the design and evaluation of an interactive MindBot to help a person deal with depressive Sentiments and to support individuals experiencing depressive symptoms by providing timely, interactive, and empathetic engagement. With the growing trend of mental health issues and a lack of adequate resources to cope, the need for innovative solutions is of great importance. In this MindBot, users will be connected to each other to communicate their Sentiments and seek support. The integration of NLP and LLMs by the chatbot fosters meaningful conversations and ensures timely support to users. Computational architecture optimizes response generation to control the processing cost related to LLMs while striking a balance between conversational richness and efficiency. This method allows for real-time communication without sacrificing the caliber of involvement. The chatbot's integration of NLP and LLMs promotes meaningful discussions and guarantees that consumers receive prompt service. The utilization of predefined response templates combined with dynamic responses generated by GPT -3.5-turbo further improved the implementation's performance in conversational capability. The paper covered the system architecture, methodology, and results achieved, with an emphasis on the contribution of sentiment analysis and the contributions of the chatbot towards mental health support. User happiness, emotional correctness, referral appropriateness, and the model's capacity to sustain coherent conversation even in the face of small user input errors are all used to gauge how effective the model is. The results indicate that the effectiveness of mental health interventions and user engagement are increased when sentiment analysis and sophisticated language models are combined. It was demonstrated that the impact of integrating advanced language models along with sentiment analysis can have a huge bearing on enhancing the user engagement factor as well as the ef

关键词： Chatbots

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Approaches for Underwater Object Classification using Sonar data 1

Machine Learning Approaches for Underwater Object Classifica...

引用

1st International Conference on Innovations in Communications, Electrical and Computer Engineering, ICICEC 2024

作者： Sowmya, B.J. Mugada, Swathi Swetha, B.N. Vijaya Kumar, B.P. Ramaiah Institute of Technology Department of Artificial Intelligence and Data Science Bangalore India

ISBN: (纸本)9798350376517

The need for analyzing a sonar dataset using machine learning algorithms arises from critical applications such as naval operations, marine exploration, and environmental monitoring. Accurate classification of underwater objects, including rocks and mines, is essential for maritime safety, environmental assessment, and underwater security. Manual interpretation of sonar data is time- consuming and error-prone, necessitating automated classification methods. By leveraging machine learning, we aim to develop robust models capable of efficiently identifying underwater objects, thereby advancing underwater sensing technology and supporting various marine-related endeavors. Here, we investigate the efficacy of Random Forest and Linear Regression machine learning algorithms in analyzing a sonar dataset comprising frequencies to predict whether an object is a rock or a mine. The primary objective is to compare the performance of these two algorithms in classifying underwater objects based on acoustic signals. By leveraging machine learning techniques, we aim to develop models capable of effectively discriminating between rocks and mines based on their acoustic signatures, thus addressing the challenge of underwater object identification. Therefore, the experimental setup involves preprocessing techniques to enhance feature extraction and mitigate noise, ensuring the robustness of the model and optimizing computational efficiency without compromising accuracy. © 2024 IEEE.

关键词： Random forests

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 << < 6 7 8 9 10 11 12 13 14 15 > >>

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：