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

11,418 篇 会议
103 篇 期刊文献
44 册 图书

馆藏范围

11,565 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

7,887 篇 工学
- 6,413 篇 计算机科学与技术...
- 3,788 篇 软件工程
- 1,496 篇 控制科学与工程
- 1,378 篇 电气工程
- 1,236 篇 信息与通信工程
- 873 篇 生物工程
- 557 篇 机械工程
- 430 篇 动力工程及工程热...
- 418 篇 生物医学工程（可授...
- 382 篇 交通运输工程
- 362 篇 电子科学与技术（可...
- 269 篇 光学工程
- 260 篇 安全科学与工程
- 236 篇 材料科学与工程（可...
- 223 篇 化学工程与技术
2,875 篇 理学
- 1,791 篇 数学
- 930 篇 生物学
- 485 篇 物理学
- 450 篇 统计学（可授理学、...
- 321 篇 系统科学
- 199 篇 化学
1,743 篇 管理学
- 1,292 篇 管理科学与工程(可...
- 586 篇 工商管理
- 537 篇 图书情报与档案管...
497 篇 医学
- 368 篇 临床医学
- 345 篇 基础医学(可授医学...
- 184 篇 药学(可授医学、理...
354 篇 教育学
- 344 篇 教育学
209 篇 法学
- 191 篇 社会学
204 篇 经济学
- 204 篇 应用经济学
113 篇 农学
28 篇 军事学
23 篇 文学
7 篇 艺术学

主题

969 篇 deep learning
869 篇 optimization
766 篇 machine learning
537 篇 accuracy
404 篇 reinforcement le...
277 篇 training
274 篇 computational mo...
269 篇 feature extracti...
263 篇 predictive model...
220 篇 real-time system...
205 篇 neural networks
202 篇 support vector m...
179 篇 particle swarm o...
150 篇 convolutional ne...
148 篇 genetic algorith...
147 篇 adversarial mach...
140 篇 machine learning...
139 篇 learning systems
133 篇 data models
131 篇 analytical model...

机构

56 篇 chitkara univers...
31 篇 chitkara centre ...
22 篇 chitkara univers...
19 篇 university of ch...
14 篇 university of sc...
14 篇 misr int univ fa...
14 篇 school of comput...
13 篇 univ chinese aca...
13 篇 institutes for r...
12 篇 centre of resear...
12 篇 al-farahidi univ...
12 篇 lviv polytech na...
11 篇 guangdong provin...
11 篇 lovely professio...
11 篇 lovely professio...
11 篇 school of comput...
11 篇 the islamic univ...
11 篇 national energy ...
11 篇 king mongkuts un...
10 篇 wuhan university...

作者

15 篇 wang tao
13 篇 liu yang
13 篇 yang yang
13 篇 wang wei
13 篇 wang hao
13 篇 liu wei
11 篇 zhang jie
10 篇 zhang tao
10 篇 lima jose
10 篇 wang lei
10 篇 li hao
9 篇 hassanien aboul ...
8 篇 shiva mehta
8 篇 zhang lei
8 篇 aleven vincent
8 篇 liu jun
8 篇 wang chao
8 篇 singh jagendra
8 篇 pereira ana i.
8 篇 nojima yusuke

语言

10,789 篇 英文
750 篇 其他
52 篇 中文
1 篇 西班牙文
1 篇 法文
1 篇 俄文
1 篇 土耳其文

检索条件"任意字段=4th Conference on Learning and Intelligent Optimization"

共 11565 条记录，以下是721-730 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：

Multi-Target Classification for Predicting Myocardial Infarction Complications: A Comparative Analysis of Various Machine learning Techniques 4

Multi-Target Classification for Predicting Myocardial Infarc...

引用

4th International Mobile, intelligent, and Ubiquitous Computing conference

作者： Elashmawi, Walaa H. Tamer, Abdullah Nasr, Ahmed Misr Int Univ Fac Comp Sci Cairo Egypt Ain Shams Univ Fac Engn Cairo Egypt

ISBN: (纸本)9798350367782;9798350367775

Myocardial Infarction (MI) poses a significant challenge due to its potential for severe complications. Accurate identification of these complications is essential for improving prognosis. this paper investigates the application of a multi-label machine learning approach to classify complications arising from MI. these complications include heart failure, arrhythmias, and cardiogenic shock. the study uses patient datasets, features such as demographic information, clinical history, and biomarker levels. By employing advanced machine learning models, including binary relevance, classifier chains, label powerset, and RAKEL-D, the research aims to enhance the predictive accuracy of MI complication diagnosis. the findings demonstrate that the RAKEL-D model outperforms other classifiers in accurately identifying concurrent complications. It shows an f1 score between 0.615 to 0.64 across five-fold, around 0.054 to 0.057 hamming loss, 0.62 Jaccard, and 0.442 accuracy.

关键词： Myocardial Infarction RAKEL-D Machine learning Multi-target classification

来源：评论

学校读者我要写书评

暂无评论

Automated Tuna Freshness Assessment via Gas Sensors and Machine learning Algorithms 4

Automated Tuna Freshness Assessment via Gas Sensors and Mach...

引用

4th International conference on intelligent Cybernetics Technology and Applications, ICICyTA 2024

作者： Pratama, Nyoman Raflly Novamizanti, Ledya Wijaya, Dedy Rahman School of Electrical Engineering Telkom University Bandung Indonesia School of Electrical Engineering Center of Excellence Artificial Intelligence for Learning and Optimization Telkom University Bandung Indonesia School of Appllied Science Telkom University Bandung Indonesia

ISBN: (纸本)9798331506490

Ensuring the safety and quality of fish products is essential for public health, especially in countries like Indonesia, where tuna is a popular fishery product. Tuna freshness is a critical indicator of seafood safety, directly influencing both its nutritional value and the risk of contamination. this study explores the application of machine learning models to accurately and efficiently classify tuna freshness based on gas emissions detected by an electronic nose (e-nose) system. the system employs MQ-135, MQ-9, and MQ-2 gas sensors, which are sensitive to spoilage-associated gases such as ammonia, methane, and alcohol. A dataset of 58,389 records was generated to capture the gas profiles released by tuna over time, creating a robust dataset for model training and validation. three machine learning algorithms-K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Naive Bayes-were compared to evaluate classification accuracy and practical applicability. Results indicate that both KNN and SVM achieved high accuracy rates of 99%, while Naive Bayes reached 90%, underscoring the suitability of KNN and SVM for tuna freshness detection. these findings demonstrate the potential of integrating e-nose technology and machine learning to provide a rapid, reliable, and scalable solution for freshness assessment in the fishing industry, enhancing quality control from suppliers to retailers. © 2024 IEEE.

关键词： Fish products

来源：评论

学校读者我要写书评

暂无评论

Innovative Practices on Machine learning Models for Statistical Interpretation 4

Innovative Practices on Machine Learning Models for Statisti...

引用

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

作者： Gunasekaran, K.R. Babu, K G Raja Sabarish Nagpal, Amandeep Aswini, Kilaru Priyadharshini, L. Niranjana, K. Saveetha Institute of Medical and Technical Science Saveetha School of Law India Sourashtra College Madurai Research Department of Business Administration Tamilnadu India Lovely Professional University Phagwara India Institute of Aeronautical Engineering Hyderabad India

ISBN: (纸本)9798350307757

this project investigates the ways in which big data, machine learning, and hyperspectral information might be used in order to enhance agricultural operations. Because hyperspectral photography offers precise spectral information for each pixel, it is now feasible to detect and evaluate a broad variety of plant conditions. this is particularly useful in light of the explosion of data related to agriculture. A new paradigm in farm management is generated when the massive storage and processing powers of big data technologies are combined with the predictive capabilities of machine learning algorithms. this research analyzes how the convergence of these technologies might revolutionize yield prediction, disease diagnosis, and crop monitoring, therefore paving the way for more intelligent and data-driven decisions to be made in the agricultural sector. © 2024 IEEE.

关键词： Crops

来源：评论

学校读者我要写书评

暂无评论

the use of Integration of H Level Communication with the Extended Identity Power Process to Have intelligent Vehicles: An Empirical Review 4

The use of Integration of H Level Communication with the Ext...

引用

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

作者： Verma, Rajan Suma, S. Radha, N. Joshi, Abhishek Shnain, Ammar Hameed Praveenkumar, C. Chitkara University Chitkara Center for Research and Development Himachal Pradesh 174103 India Cmr Technical Campus Department of Cse Telangana Hyderabad India Aditya Engineering College Department of Electronics and Communication Engineering Surampalem India Uttaranchal University School of Liberal Arts Department of Liberal Arts Dehradun248007 India The Islamic University Najaf Iraq Sri Ramakrishna Engineering College Department of Eee Coimbatore India

ISBN: (纸本)9798350360165

the arrival of sixth-generation (6 G) wireless technology has ushered in a new era of connectivity, promising innovative services such as the Internet of things (IoT) and, more importantly, when it is stimulating research into sixthgeneration networks (6G). However, the widespread integration of artificial intelligence (AI) into intelligent vehicles faces significant challenges. these challenges include limited resources, lack of high-quality labelled data, and lack of AIoptimized architecture. Edge Intelligence is emerging as a promising solution that aims to seamlessly integrate artificial intelligence with intelligent vehicles. this paper describes the key requirements and trends driving the understanding of 6 G networks, with an emphasis on self-learning techniques to develop intelligent vehicles. this study suggests a framework focused on automated learning based on onboard awareness, with the goal of reducing human intervention by automating data processing and model development. this architecture uses a Generative Adversarial Network (GAN) to aggregate labelled data for Al training, ensuring scalability, adaptability and efficiency. A case study in a connected traffic network demonstrates the effectiveness of the architecture for intelligent vehicles. the proposed architecture not only addresses the challenges of 6 G networks but also aligns with their requirements for efficiency, adaptability, and human-centricity By leveraging self-learning mechanisms, it paves the way for autonomous adaptation and evolution in dynamic network environments. © 2024 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Early Detection of Parkinsons Using Machine learning 4

Early Detection of Parkinsons Using Machine Learning

引用

4th International conference on Emerging Systems and intelligent Computing, ESIC 2024

作者： Manoj Kumar, D. Arthi, R. Rajeev, Akshay Ranjith, Adithya Murali, Ashwin Arjun, K. Srm Institute of Science and Technology Department of Electronics and Communication Engineering Ramapuram Campus Chennai India

ISBN: (纸本)9798350349856

Biomarkers derived from human voice can offer in-sight into neurological disorders, such as Parkinson's disease (PD), because of their underlying cognitive and neuromuscular function. Historically, PD has been difficult to quantity and doctors have tended to focus on some symptoms while ignoring others, relying primarily on subjective rating scales. With advancements in technology and the prevalence of audio collecting devices in daily lives, reliable models that can translate this audio data into a diagnostic tool for healthcare professionals would potentially provide diagnoses that are cheaper and more accurate. this project provides evidence to validate this concept here using a voice dataset collected from people with and without PD. this paper explores the effectiveness of using extreme gradient boosting algorithms, such as XG boost algorithm, to accurately diagnose individuals with the disease Researchers have found that this term is a basic term for a PD More recently, learning Machines (MLs) have helped solve computer vision problems, process natural languages, recognize Parkinson's speech using machine learning tools and provide a better understanding of the PD database in the current decade. Parkinson's voice database is available at UCI machine storage in the center of learning equipment and intelligent programs. the major outcome of this project is to bring out the result with the most accuracy using XG boost Algorithm. the database contains the similar links show high variability in the Parkinson's disease database. the most importantly the comparison has been made to explicit the outcome result and to prove that the XG boost algorithm provides more accuracy comparing with other algorithms. © 2024 IEEE.

关键词： Database systems

来源：评论

学校读者我要写书评

暂无评论

Path planning of mobile robot based on improved ant colony optimization algorithm 4

Path planning of mobile robot based on improved ant colony o...

引用

4th International conference on Artificial Intelligence, Robotics, and Communication, ICAIRC 2024

作者： Zhu, Baiqiang Luo, Xi Huang, Rongxin Lu, Fangyao Yanshan University School of Electrical Engineering Qinhuangdao China Beijing Institute of Technology School of Physics Beijing China

ISBN: (纸本)9798331531225

Path planning for mobile robots is a critical research area in intelligent control and automation. To address the issues of slow convergence and susceptibility to local optima in traditional ant colony algorithms within complex environments, this paper introduces a series of improvement strategies. An attenuation function is incorporated to optimize heuristic information, enabling ants to rely more on pheromone-based decision-making in the later stages. Directional guidance angles are added to enhance the directivity of state transition probabilities, accelerating the path search process. Additionally, cubic B-spline curves are employed to smooth the paths, while the 2-opt algorithm is integrated to further minimize path lengths. these enhancements significantly improve the algorithm's efficiency and stability. Simulation results validate the superiority of the proposed algorithm in path planning performance, offering an effective solution for optimizing mobile robot navigation in complex environments. © 2024 IEEE.

关键词： Ant colony optimization

来源：评论

学校读者我要写书评

暂无评论

A comprehensive review of recent advances and challenges in artificial intelligence and machine learning 4th

A comprehensive review of recent advances and challenges in ...

引用

4th International conference on Computational Methods in Science and Technology, ICCMST 2024

作者： Singla, Ishdeep Hans, Aarti Smiksha Diya Swami, Harsh Kumar Ranjan, Rahul Computer Science and Engineering Chandigarh University Mohali Gharuan India

ISBN: (纸本)9781032911571

Modern advances in Artificial Intelligence (AI) and Machine learning (ML) have transformed many businesses and elements of everyday life. Machine learning and deep learning support disease diagnosis, drug development, and patient risk assessment. this study examines how healthcare organizations evaluate enormous data sets using machine learning. this paper examines pros and downsides of current methods and research obstacles. Our goal is to educate healthcare professionals and government organizations on machine learning-based big data analytics in intelligent healthcare. AIML-powered chatbots enable governments educate and serve residents. they assist people get permits, answer questions, and use government services. Assistants help students make appointments, answer inquiries, and offer course material. Lead generation, product recommendations, and marketing efforts using AIML chatbots may boost revenue. AIML helps companies make data-driven decisions, find patterns, and recognize trends using data analysis and predictive analytics. Machine learning studies how computers learn and improve without programming. Machine learning (ML) is a very captivating technology that has garnered significant interest over the course of technological advancements. As indicated by its nomenclature, this attribute endows the computer with a capacity that enhances its resemblance to human behaviour: the ability to acquire knowledge. © 2025 the Author(s).

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Improving System Security: Machine learning Algorithm-Based Intrusion Detection System 4

Improving System Security: Machine Learning Algorithm-Based ...

引用

4th International conference on Ubiquitous Computing and intelligent Information Systems, ICUIS 2024

作者： Barpute, Jyotsna Vilas Bhargava, Sanjay Mansarovar Global University Faculty of Engineering and Technology Department of Computer Science Bhopal India Dr. D. Y. Patil Institute of Technology Pimpri Pune India

ISBN: (纸本)9798331529635

In today's era, computer technology is now required in many areas of our daily lives, including banking, entertainment, education, and communication. System security is crucial in the digital age, and detecting intrusion threats is the most difficult problem. Cyber- attacks put data availability, confidentiality, and integrity at risk and make it more difficult to identify intrusions exactly. An intrusion detection system is a method that keeps an eye out for unusual activity on the network and sends out an alarm when it finds it. the paper compares Intrusion Detection System (IDS) taxonomy, an indepth analysis of intrusion detection methods, and widely used evaluation datasets. In order to decrease false positives, find new threats, and effectively detect intruders, researchers work to improve IDS. IDS systems use machine learning (ML) techniques because they have the ability to effectively detect network intrusions. the study examines the most recent developments and trends in machine learning-based hybrid intrusion detection systems (HIDS). Numerous methods have emerged for intrusion detection that make use of the machine learning methodology. Combining results from a comparison survey of different machine learning algorithms, the decision tree-which is renowned It is recommended as a model for discovering result abnormalities due to its quickness and simplicity of usage. © 2024 IEEE.

关键词： Network intrusion

来源：评论

学校读者我要写书评

暂无评论

Machine learning-Based Ship Energy Efficiency Algorithms 4

Machine Learning-Based Ship Energy Efficiency Algorithms

引用

4th International conference on Energy, Power and Electrical Engineering, EPEE 2024

作者： Zhang, Defu Chen, Mengqin Zhu, Wei Lv, Hongbin Tianjin University of Technology Maritime College Tianjin China Tianjin University of Technology Paper Union and other carbon ship technology research centers Tianjin China Yingkou AtoN Division Northern Navigation Service Center Liaoning Yingkou China Co. Ltd Tianjin China

ISBN: (纸本)9798331518066

this paper establishes fuel consumption prediction models using the Random Forest algorithm (RF) and Deep Neural Network (DNN) algorithm, with the models' performance evaluated based on Mean Square Error (MSE) and the coefficient of determination (R2). On this basis, a speed optimization model is developed using a DQN algorithm to dynamically adjust speed for minimizing fuel consumption. the evaluation of the model is conducted through the accumulation of reward values. the results show that the fuel consumption prediction model built using the RF algorithm achieves an MSE of 0.00064 and an R2 of 0.99781. the model constructed with the DNN algorithm yields an MSE of 0.00516 and an R2 of 0.99799. Comparatively, the RF algorithm slightly outperforms the DNN. Finally, the speed optimization model developed using the DQN algorithm learns the optimal policy through interactions with the environment to maximize the expected accumulated reward, ultimately enhancing energy efficiency by optimizing speed in the given environmental data. © 2024 IEEE.

关键词： Deep Neural Networks Q-learning Ship Energy Efficiency Speed optimization

来源：评论

学校读者我要写书评

暂无评论

Research on Storage Performance optimization of New Power Materials Based on MGF 4th

Research on Storage Performance Optimization of New Power Ma...

引用

4th International conference on Advanced intelligent Technologies, ICAIT 2023

作者： Zhou, Rencai Xu, Yu Ningbo Yongyao Power Investment Co. Ltd Ningbo China

ISBN: (纸本)9789819732098

the performance optimization of new power materials is of great significance for improving the efficiency of traditional power equipment and reducing energy consumption and environmental pollution. New power materials are widely used in the field of manufacturing, transportation, storage, and utilization of power, such as high-temperature superconductors, photovoltaic cells, and lithium-ion batteries. the performance of these materials has a direct impact on the development of the entire industry and the sustainable development of human society. Optimizing the performance of new electric power materials can improve its electrical conductivity, heat transfer, mechanical strength, corrosion resistance, and other characteristics, so as to improve the efficiency and safety of electric power equipment and reduce resource waste and environmental pollution. However, existing research on storage performance optimization of equipment is mostly based on traditional methods. Nowadays, with the rapid development of deep learning technology, traditional methods can no longer meet the needs of the Times. therefore, this paper proposes a neural network-based performance optimization research method of MGF new power material equipment. First, we use deep learning method to complete the end-to-end power prediction. In the power-upgrading task, we propose a correction model based on multi-grain cascade forest and fuzzy control rules to correct the prediction results. Finally, the reliability of our model is proved by experiments. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： High temperature superconductors

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 << < 69 70 71 72 73 74 75 76 77 78 > >>

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：