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

3,259 篇 会议
56 册 图书
24 篇 期刊文献

馆藏范围

3,339 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,736 篇 工学
- 1,337 篇 计算机科学与技术...
- 1,225 篇 软件工程
- 212 篇 控制科学与工程
- 210 篇 信息与通信工程
- 197 篇 电气工程
- 153 篇 机械工程
- 135 篇 材料科学与工程（可...
- 132 篇 安全科学与工程
- 127 篇 生物工程
- 126 篇 生物医学工程（可授...
- 94 篇 土木工程
- 93 篇 交通运输工程
- 85 篇 建筑学
- 79 篇 动力工程及工程热...
- 75 篇 电子科学与技术（可...
- 70 篇 化学工程与技术
- 62 篇 力学（可授工学、理...
709 篇 理学
- 498 篇 数学
- 173 篇 统计学（可授理学、...
- 131 篇 生物学
- 115 篇 物理学
- 113 篇 系统科学
- 60 篇 化学
390 篇 管理学
- 281 篇 管理科学与工程(可...
- 172 篇 图书情报与档案管...
- 128 篇 工商管理
94 篇 医学
- 86 篇 基础医学(可授医学...
- 81 篇 临床医学
56 篇 经济学
- 56 篇 应用经济学
52 篇 教育学
- 51 篇 教育学
43 篇 法学
32 篇 农学
6 篇 文学
5 篇 军事学
1 篇 艺术学

主题

971 篇 predictive model...
282 篇 accuracy
268 篇 data models
240 篇 computational mo...
208 篇 analytical model...
182 篇 prediction algor...
149 篇 training
138 篇 software enginee...
136 篇 feature extracti...
121 篇 software
120 篇 machine learning
118 篇 deep learning
108 篇 forecasting
105 篇 neural networks
103 篇 adaptation model...
84 篇 optimization
83 篇 machine learning...
82 篇 mathematical mod...
75 篇 real-time system...
62 篇 support vector m...

机构

10 篇 school of inform...
7 篇 national enginee...
7 篇 hubei key labora...
7 篇 school of electr...
7 篇 school of automa...
6 篇 school of comput...
6 篇 school of softwa...
6 篇 school of electr...
6 篇 engineering rese...
5 篇 school of comput...
5 篇 school of transp...
5 篇 nanjing univ sta...
5 篇 chitkara univers...
5 篇 school of softwa...
4 篇 school of inform...
4 篇 naval university...
4 篇 school of manage...
4 篇 school of softwa...
4 篇 software enginee...
4 篇 school of electr...

作者

8 篇 labiche yvan
7 篇 hassan ahmed e.
7 篇 menzies tim
5 篇 yang yang
5 篇 mcintosh shane
5 篇 chen li
5 篇 ziadi tewfik
5 篇 yan wang
4 篇 yu wang
4 篇 ming li
4 篇 liu yang
4 篇 hall tracy
4 篇 xintian liu
4 篇 bowes david
4 篇 monden akito
4 篇 min wu
4 篇 matsumoto ken-ic...
4 篇 yu zhang
4 篇 lei zhang
4 篇 briand lionel c.

语言

3,043 篇 英文
285 篇 其他
25 篇 中文
1 篇 俄文

检索条件"任意字段=Proceedings of the 6th International Conference on Predictive Models in Software Engineering"

共 3339 条记录，以下是811-820 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：

Implementing and Evaluating a P4-based Access Gateway Function on a Tofino Switch

Implementing and Evaluating a P4-based Access Gateway Functi...

引用

international conference on Advanced Communication Technologies and Networking (CommNet)

作者： El-Mehdi Makhroute Mohammed-Ayoub Elharti Vincent Brouillard Yvon Savaria Tarek Ould-Bachir Department of Computer and Software Engineering Polytechnique Montréal Montreal Canada Department of Electrical Engineering Polytechnique Montréal Montreal Canada

this paper introduces an Access Gate Function (AGF) that has been implemented using the P4 language and evaluates its performance when running on a Tofino switch. through the process of translating specifications from the Broadband Forum (BBF) for Fixed Mobile Convergence in the 5G Core into a P4 code and by conducting data plane simulations on software switch models, we provide evidence that the AGF solution conforms to industry standards and exhibits efficient and scalable performance characteristics. Subsequently, we assess the prototype’s implementation on a Tofino switch, analyzing its capabilities and limitations. the reported results demonstrate that the programmable P4 Tofino switch efficiently handles a significant number of sessions, further reinforcing the potential and practicality of the proposed solution for industrial deployment in fixed-mobile convergence scenarios.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Adapting Speech models for Stock Price Prediction

Adapting Speech Models for Stock Price Prediction

引用

Cybernetics, Cognition and Machine Learning Applications (ICCCMLA), IEEE international conference on

作者： Frederic Voigt Jose Alcarez Calero Keshav Dahal Qi Wang Kai von Luck Peer Stelldinger Department of Computer Science University of the West of Scotland / Hamburg University of Applied Sciences Hamburg Germany School of Computing Engineering & Physical Sciences University of the West of Scotland Paisley Scotland Department of Computer Science Hamburg University of Applied Sciences Hamburg Germany

ISBN: (数字)9798331505790

ISBN: (纸本)9798331505806

Large language models (LLMs) have demonstrated remarkable success in the field of natural language processing (NLP). Despite their origins in NLP, these algorithms possess the theoretical capability to process any data type represented in an NLP-like format. In this study, we use stock data to illustrate three methodologies for processing regression data with LLMs, employing tokenization and contextualized embeddings. By leveraging the well-known LLM algorithm Bidirectional Encoder Representations from Transformers (BERT) [1], we apply quantitative stock price prediction methodologies to predict stock prices and stock price movements, showcasing the versatility and potential of LLMs in financial data analysis.

关键词： Adaptation models Machine learning algorithms Large language models Machine learning predictive models Transformers Prediction algorithms Tokenization Encoding Speech processing

来源：评论

学校读者我要写书评

暂无评论

A Comparative Study of Photovoltaic Power Prediction models Based on BP and SVR

A Comparative Study of Photovoltaic Power Prediction Models ...

引用

Robotics, Intelligent Control and Artificial Intelligence (RICAI), international conference on

作者： Feng Lu Zhen Li Xin Wang Lei Zhao Fei Meng Guohua Yang Dispatching & Control Center of State Grid Ningxia Power Co. Ltd Yinchuan Ningxia China School of Electronic and Electrical Engineering Ningxia University Yinchuan Ningxia China

ISBN: (数字)9798331541699

ISBN: (纸本)9798331541705

the power output of photovoltaic (PV) generation is influenced by various environmental factors, exhibiting non-linearity and uncertainty. this paper constructs photovoltaic power prediction models based on BP neural network and support vector regression (SVR) algorithms, and performs a comparative analysis of model performance using metrics such as root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R 2 ). the results show that the BP neural network is suitable for handling complex nonlinear large-scale data, while SVR demonstrates higher accuracy and generalization ability under small sample conditions. this study provides a reference for the selection and optimization of photovoltaic power prediction models.

关键词： Photovoltaic systems Support vector machines Analytical models Accuracy Processor scheduling Computational modeling Neural networks predictive models Computational efficiency Forecasting

来源：评论

学校读者我要写书评

暂无评论

Data-Driven Risk Measurement by SV-GARCH-EVT Model

Data-Driven Risk Measurement by SV-GARCH-EVT Model

引用

Data-driven Optimization of Complex Systems (DOCS), international conference on

作者： Shi Bo Minheng Xiao dept. Mathematics and Statistics xsBoston University Boston USA dept. Integrated System Engineering Ohio State University Columbus USA

ISBN: (数字)9798350377842

ISBN: (纸本)9798350377859

this paper aims to more effectively manage and mitigate stock market risks by accurately characterizing finan-cial market returns and volatility. We enhance the Stochastic Volatility (SV) model by incorporating fat-tailed distributions and leverage effects, estimating model parameters using Markov Chain Monte Carlo (MCMC) methods. By integrating extreme value theory (EVT) to fit the tail distribution of standard residuals, we develop the SV-EVT-VaR-based dynamic model. Our empirical analysis, using daily S&P 500 index data and simulated returns, shows that SV-EVT-based models outperform others in backtesting. these models effectively capture the fat-tailed properties of financial returns and the leverage effect, proving superior for out-of-sample data analysis.

关键词： Reactive power Analytical models Pandemics Stochastic processes Tail predictive models Prediction algorithms Data models Stock markets Standards

来源：评论

学校读者我要写书评

暂无评论

Next-Gen Breast Cancer Prediction through Adaptive Deep Learning

Next-Gen Breast Cancer Prediction Through Adaptive Deep Lear...

引用

Mobile Computing and Sustainable Informatics (ICMCSI), international conference on

作者： Pandarinath Potluri Kavyashree Nagarajaiah K.Mohana Lakshmi Manjula Moolbharathi Nagaratnamma Allam Balaram Department of CSE Swarnandhra college of engineering and technology Department of MCA Sri Siddhartha Institute of Technology Tumkur Department of ECE CMR Technical Campus Hyderabad Telangana India govt polytechnic Afzalpur Kalaburgi Karnataka Department of CSE MLR Institute of Technology Hyderabad

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522674

this study enhances the ongoing advancements in breast cancer diagnostic tools by highlighting the importance of employing adaptive deep learning and optimization strategies to achieve high accuracy rates. Advancements in medical technology have facilitated early diagnosis and enhanced treatment outcomes for breast cancer, potentially providing doctors with a valuable tool for early detection that could significantly improve patient outcomes. this study introduces a novel approach, Learning Assisted Breast Cancer Prediction (LABCP), which incorporates an advanced ensemble of Cascaded Inception Model and the Ant Lion Optimization algorithm. the proposed adaptive deep learning scheme harnesses the power of deep neural networks to enhance breast cancer prediction accuracy. the experimental evaluation demonstrates outstanding predictive performance, with an accuracy of 98%. the Cascaded Inception Model effectively captures intricate features within breast cancer images, while the Ant Lion Optimization algorithm optimizes the model parameters, further refining the predictive capability. the combination of these techniques results in a robust and efficient system for early breast cancer detection.

关键词： Deep learning Adaptation models Accuracy Adaptive systems Refining Artificial neural networks predictive models Prediction algorithms Breast cancer Optimization

来源：评论

学校读者我要写书评

暂无评论

Electricity Load Forecasting Based on Patch Channel-Mixing Transformer Model

Electricity Load Forecasting Based on Patch Channel-Mixing T...

引用

international conference on Electronic engineering and Informatics (EEI)

作者： Jiwei Xing Xinying Xu Chao Liu Dongmei Hu School of Electrical and Power Engineering Taiyuan University of Technology Taiyuan China

ISBN: (数字)9798350353594

ISBN: (纸本)9798350353600

Recent research has demonstrated the strong potential of Transformer models in electricity load forecasting, due to their ability to effectively address the long-term memory modeling issues in the load forecasting process. However, there are several issues with Transformer models for load forecasting, including quadratic time complexity, difficulty in screening factors with electricity load, and false similarity points due to the modeling methods on point level. To address those issues, we propose an efficient design of Transformer-based model for electricity load forecasting. It is based on two components: (i) divide the load sequence and multi-factor sequence into subsequence level segments with multiple resolutions, and then use them as input markers for the Transformer model. (ii) channel mixing, where the load channel interacts with multiple factors channels to achieve explicit modeling of the relationship between load and multiple factors. Extensive experiments have demonstrated that our model significantly outperforms existing methods on two large-scale datasets, and provide a new solution to the load forecasting problem.

关键词： Training Accuracy Load forecasting Electricity Noise predictive models Transformers Time complexity Informatics Load modeling

来源：评论

学校读者我要写书评

暂无评论

Performance Analysis of Machine Learning Algorithms Using Bagging Ensemble Technique for software Fault Prediction

Performance Analysis of Machine Learning Algorithms Using Ba...

引用

international conference on Information Systems and Computer Networks (ISCON)

作者： Roshan Samantaray Himansu Das School of Computer Engineering KIIT Deemed to be University Bhubaneswar India

software development comes with a lot of challenges. Developers face various issues with performance and bugs. these issues increase with the scale of the project and if fewer individuals work on the development. It has become necessary to fix various bugs during development to ensure better performance and reduce the chances of failure during the deployment of the software. As a result of this, faults in the software must be predicted during the earlier stages of development. this would help in reducing the cost of maintenance of the software post-deployment. Multiple software fault prediction (SFP) approaches have been proposed to tackle this problem. these approaches can be improved by implementing ensemble techniques. In this paper, we study the effect of the bagging technique and how it helps to improve the predictive capability across various datasets. these datasets are provided and made open source by NASA. Decision Tree Classifier (DTC), Logistic Regression (LR), K-Nearest Neighbors (KNN), Gaussian Naive Bayes (GNB), and Support Vector Classifier (SVC) were used as base classifiers for the bagging method. Random forest (RFC) is an ensemble learning algorithm that uses the bagging technique. Based on the outcome of the results, it was concluded that RFC was the best-performing algorithm.

关键词： Machine learning algorithms software algorithms NASA Support vector machine classification Static VAr compensators Gaussian processes Prediction algorithms

来源：评论

学校读者我要写书评

暂无评论

Traffic Flow Prediction Method Based on Hybrid Adaptive Graph Convolutional Network

Traffic Flow Prediction Method Based on Hybrid Adaptive Grap...

引用

international conference on Communications, Information System and Computer engineering (CISCE)

作者： Jianhua Ren Lei Gao School of Electronic and Information Engineering Liaoning Technical University Huludao Liaoning China

ISBN: (数字)9798350353174

ISBN: (纸本)9798350353181

Aiming at the problems that the explicit graph structure in the short-time traffic flow prediction model does not necessarily reflect the real dependency relationship and cannot effectively discriminate the high-frequency information in the short-time sequence, a novel traffic flow prediction approach leveraging a hybrid adaptive graph convolutional network is introduced. Firstly, a spatial information extraction module that can obtain different relationship features among nodes is introduced, which is used to solve the problem of too single spatial information extraction. Secondly, a temporal convolution module with local high-frequency information extraction is proposed to better identify the high-frequency effects in the traffic flow. Lastly, the spatial and temporal extraction modules are connected in parallel to form the spatiotemporal network layer, which is finally connected to the output layer to obtain the prediction. three real traffic datasets are used for the experiments, and compared with the existing mainstream models, the MAE, RMSE, and MAPE indexes have been improved by an average of 4.480%,3.744%, and 1.913%. It fully demonstrates that the method in this paper is effective for short-term traffic flow prediction.

关键词： Adaptation models Adaptive systems Graph convolutional networks Convolution predictive models Information retrieval Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Evaluating Feature Prioritization in a Reduced Feature Set Using Explainable AI for Intracranial Aneurysm Classification

Evaluating Feature Prioritization in a Reduced Feature Set U...

引用

international conference on Advancements in Computational Sciences (ICACS)

作者： Iram Abdullah Ali Javed Department of Computer Science Air University Kamra Pakistan Department of Software Engineering University of Engineering & Technology Taxila Pakistan

ISBN: (数字)9798331533038

ISBN: (纸本)9798331533045

the timely management of an unruptured aneurysm can prevent hemorrhage. Multiple anatomical, morphological, and hemodynamic features associated with an aneurysm can predict the risk of rupture and classify the nature of the aneurysm as either ruptured or unruptured. However, considering all features may create ambiguities in the model due to inter-dependencies, such as the correlation between aneurysm height and width to aneurysm area. In computer-aided medical diagnostics, focusing on relevant features that diagnose the disease is more crucial than using an abundance of features that may not contribute to the diagnosis and may cause unnecessary complexity. the use of independent or sparsely correlated features improves the accuracy of the classifier. the proposed research analyzes the interdependency of features by calculating the correlation between features. Based on the analyses, the high correlation threshold is determined through rigorous experimentation. From the highly correlated features, one feature is selected. Consequently, the reduced feature set is recommended. the reduced feature set performs better with simpler classifiers. Instead of choosing a classifier that struggles with a broad range of features, an appropriately optimized feature set can enhance performance and improve accuracy. the proposed approach is tested on a publicly available dataset of aneurysms, leading to an improvement in classification accuracy from 82.6% to 87%, due to the use of an appropriate feature set. Moreover, the best model was evaluated using two different explainable AI frameworks to assess the contribution of each feature in prediction. However, the conflicting feature prioritization in each explainable framework suggests that these models prioritize different features for the same trained model, leading to ambiguity. this inconsistency indicates that the explainable models lack generalization and fail to consistently analyze feature importance.

关键词： Accuracy Correlation Explainable AI Computational modeling Redundancy Training data Aneurysm predictive models Medical diagnosis Random forests

来源：评论

学校读者我要写书评

暂无评论

Time Delay Estimation model and Robot Network Control Research

Time Delay Estimation model and Robot Network Control Resear...

引用

Internet of things, Automation and Artificial Intelligence (IoTAAI), international conference on

作者： Kemin Wang Feng Xu School of Electrical and Information Engineering Guangdong Baiyun University Guangzhou China

ISBN: (数字)9798350386974

ISBN: (纸本)9798350386981

When robots and affiliates work together, there is a practical demand for third-party software platform centralized scheduling control. In this paper, a robot control scheme based on maximum delay estimation model is proposed to solve the problem of network communication delay between robot controller and thid-party software platform. Firstly, the function model, data model, structure model and behavior mechanism of network control module ara analyzed, and the QTcpSocket class is used to establish communication connnection and send receive network packets. A set of network conmunication mechanism based on delay model is designed and developed. this scheme has been successfully applied in the 3D reconstruction projects of 3D scanner and robot. It realizes the stable control of the robot and the affiliated operation mechanism by the PC human-machine interface, and achieves the expected goals of the effectiveness of collaborative tasks, accurate command response and reasonable avoidance of misactions.

关键词： Analytical models three-dimensional displays Human-machine systems Robot control Estimation Delay estimation Data models software Internet of things Robots

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334页 << < 78 79 80 81 82 83 84 85 86 87 > >>

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：