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

3,503 篇 会议
67 篇 期刊文献
9 册 图书

馆藏范围

3,579 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,450 篇 工学
- 2,019 篇 计算机科学与技术...
- 1,187 篇 软件工程
- 621 篇 信息与通信工程
- 517 篇 电气工程
- 441 篇 生物工程
- 384 篇 生物医学工程（可授...
- 382 篇 控制科学与工程
- 163 篇 电子科学与技术（可...
- 150 篇 光学工程
- 107 篇 机械工程
- 86 篇 材料科学与工程（可...
- 81 篇 石油与天然气工程
- 74 篇 安全科学与工程
- 67 篇 化学工程与技术
- 66 篇 仪器科学与技术
- 64 篇 网络空间安全
- 59 篇 交通运输工程
1,002 篇 理学
- 490 篇 数学
- 468 篇 生物学
- 234 篇 物理学
- 157 篇 统计学（可授理学、...
- 89 篇 化学
- 86 篇 系统科学
440 篇 管理学
- 280 篇 管理科学与工程(可...
- 200 篇 图书情报与档案管...
- 130 篇 工商管理
369 篇 医学
- 318 篇 基础医学(可授医学...
- 174 篇 临床医学
- 102 篇 药学(可授医学、理...
- 88 篇 公共卫生与预防医...
61 篇 法学
59 篇 经济学
57 篇 农学
39 篇 教育学
3 篇 文学
3 篇 军事学
1 篇 艺术学

主题

769 篇 neural networks
616 篇 convolutional ne...
272 篇 deep learning
215 篇 training
187 篇 artificial intel...
179 篇 accuracy
162 篇 feature extracti...
159 篇 artificial neura...
146 篇 recurrent neural...
125 篇 predictive model...
123 篇 deep neural netw...
108 篇 computational mo...
99 篇 machine learning
88 篇 data models
64 篇 neural network
60 篇 real-time system...
59 篇 support vector m...
57 篇 generative adver...
57 篇 analytical model...
56 篇 convolution

机构

23 篇 chitkara univers...
16 篇 chitkara centre ...
13 篇 centre for resea...
12 篇 sr university sc...
10 篇 pune
10 篇 the islamic univ...
9 篇 department of el...
8 篇 chitkara univers...
8 篇 chitkara univers...
8 篇 univ zurich inst...
8 篇 swiss fed inst t...
8 篇 college of engin...
8 篇 department of co...
7 篇 college of infor...
7 篇 school of comput...
6 篇 chitkara univ in...
6 篇 saveetha institu...
6 篇 school of comput...
6 篇 swiss fed inst t...
5 篇 faculty of engin...

作者

7 篇 kumar deepak
7 篇 indiveri giacomo
6 篇 pareek piyush ku...
6 篇 donati elisa
6 篇 kumar bura vijay
5 篇 murata j
5 篇 pedrycz witold
5 篇 pratham kaushik
5 篇 kukreja vinay
5 篇 prateek verma
5 篇 liu shih-chii
5 篇 orchard garrick
5 篇 hirasawa k
5 篇 masrour tawfik
4 篇 piazza f
4 篇 wang lei
4 篇 madani kurosh
4 篇 neftci emre
4 篇 delbruck tobi
4 篇 sunil g.

语言

3,443 篇 英文
128 篇 其他
26 篇 中文
1 篇 西班牙文

检索条件"任意字段=2nd IASTED International Conference on Neural Networks and Computational Intelligence"

共 3579 条记录，以下是21-30 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：

Research on the application of neural networks for detecting financial reporting fraud 2

Research on the application of neural networks for detecting...

引用

2nd international conference on Big Data, computational intelligence, and Applications, BDCIA 2024

作者： Lin, Huijuan Zhuang, Yirong Zhang, Jie Wen, Xiaohao Guangdong Polytechnic Foshan China Zhuhai Guancheng Chemical Trade Co. Ltd. Zhuhai China Guangxi Normal University Guilin China

ISBN: (纸本)9781510689053

This research investigates the application of neural networks in addressing the increasingly prevalent issue of financial fraud among publicly listed companies. With the growing number of such companies and heightened economic pressures, fraud detection has become a critical concern. Leveraging a dataset from the Taian database, this study analyzes financial data from 3, 032 companies, comprising 723 fraudulent and 2, 309 non-fraudulent entities. A key contribution of this work is the integration of principal component analysis with neural network modeling to enhance the detection process. The neural network model is trained and validated using 27 carefully selected financial indicators, such as net accounts receivable, inventory levels, total liabilities, and equity metrics, to identify fraudulent patterns. The model demonstrates a superior accuracy of 87.1%, outperforming traditional methods in distinguishing between fraudulent and non-fraudulent companies. This research advances the application of neural networks in the financial domain, providing an innovative, data-driven solution for fraud detection. The technical approach presented offers significant implications for improving the robustness and reliability of fraud detection mechanisms, particularly for stakeholders in regulatory, investment, and accounting fields. © 2025 SPIE.

关键词： Decentralized finance

来源：评论

学校读者我要写书评

暂无评论

SUBIINA: Stress and Unhappiness Behavioural Identification using Intelligent Artificial neural networks and Analysis 2

SUBIINA: Stress and Unhappiness Behavioural Identification u...

引用

2nd international conference on computational intelligence, Communication Technology and Networking, CICTN 2025

作者： Kandel, Abhishek Bhandari, Nishchit Kaur, Mandeep Rakesh, Nitin Gulhane, Monali Dahal, Rohsish Department of CSE School of Engineering and Technology Sharda University Uttar Pradesh Greater Noida India Department of Science Kathmandu Model Secondary School Baagbazar Bagmati Pradesh Kathmandu Nepal School of Computer Science Engineering and Technology Bennett University Uttar Pradesh Greater Noida India Department of CSE Symbiosis Institute of Technology Nagpur Campus Nagpur India Pune India

ISBN: (纸本)9798331530389

This paper presents an overview of recent research on stress detection using speech and facial expression analysis. The utilization of speech and facial expressions for the purpose of stress detection has garnered considerable interest in recent times, largely due to their non-invasive and cost-effective characteristics. The paper provides a brief introduction to the physiological and psychological aspects of stress and how it affects speech and facial production. Various approaches to stress detection using speech and facial expression analysis are discussed, including acoustic, prosodic, linguistic, and visual features. The paper also discusses the challenges associated with stress detection using speech and facial expression analysis and potential applications of this technology. In conclusion, the paper discusses future research directions in this domain, which include the creation of stress detection models that are even more precise and dependable, as well as their integration into real-world applications. © 2025 IEEE.

关键词： Speech analysis

来源：评论

学校读者我要写书评

暂无评论

Prediction method for foreign language teaching achievement utilizing an enhanced BP neural Network 2

Prediction method for foreign language teaching achievement ...

引用

2nd international conference on Big Data, computational intelligence, and Applications, BDCIA 2024

作者： Lin, Zhutian Fuzhou University of International Studies and Trade Fuzhou350202 China

ISBN: (纸本)9781510689053

With the rapid development of digital technology, online learning has become an important way for students, especially those majoring in foreign languages, to learn. To improve the accuracy of predicting student grades in foreign language teaching, a backpropagation neural network optimization model based on particle swarm optimization algorithm is proposed. Starting from the analysis of students' online learning behavior sequences, this study extracts the characteristics of online learning behavior sequences, optimizes the weights and biases of backpropagation neural networks through particle swarm optimization algorithm, and constructs a student performance prediction model. The experimental results showed that the mean square error of the proposed model in the third round of training was 0.1834, significantly lower than that of the comparison model. In practical applications, the model shows good performance in predicting the grades of three classes, with an average prediction accuracy of over 80% for Class 1, Class 2, and Class 3, which are 81.25%, 82.03%, and 86.07%, respectively. The experiment shows that the proposed model has a high prediction accuracy. The study provides an effective method for predicting grades for foreign language educators, which helps teachers adjust teaching strategies in a timely manner based on students' learning situations. © 2025 SPIE.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

Research on multi-dimensional data stream cloud platform resource scheduling and management based on deep neural networks 2

Research on multi-dimensional data stream cloud platform res...

引用

2nd international conference on Big Data, computational intelligence, and Applications, BDCIA 2024

作者： Luo, Weifeng Ren, Binhua Qiu, Ziliang Deng, Wei Qin, Siyuan Huang, Juzheng Liu, Xuezhi Shenzhen Power Supply Co. Ltd. Guangdong Shenzhen518000 China

ISBN: (纸本)9781510689053

The advent of multi-dimensional data streams is a direct result of the fast evolution of big data and cloud computing. To keep cloud platforms running smoothly, effective and dynamic management of resources is essential. on order to maximize performance, this study suggests a new way to schedule and manage resources on cloud platforms that uses deep neural networks (DNNs). The technique is tailored to multi-dimensional data streams. Resource allocation decisions may be made adaptively using real-time data analysis through the use of deep learning techniques, especially deep neural networks. The suggested approach is an attempt to make cloud computing systems more efficient by making better use of available resources and decreasing latency. The benefits of DNNs for forecasting patterns of resource demand, the function of data stream processing, and the design of the scheduling model are described in depth in the presented framework. Extensive trials show that the suggested method outperforms more conventional approaches, including round-robin and greedy algorithms, in terms of how quickly tasks are completed, how efficiently resources are used, and how scalable the system is. The results suggest that the application of DNNs in cloud platform resource management can significantly improve performance in real-world scenarios with complex, high-volume data streams. © 2025 SPIE.

关键词： Cloud platforms

来源：评论

学校读者我要写书评

暂无评论

Research on GSEm-Net detection method of embroidery pattern lightweight operator for digital protection of Gansu intangible cultural heritage Long Embroidery 2

Research on GSEm-Net detection method of embroidery pattern ...

引用

2nd international conference on Big Data, computational intelligence, and Applications, BDCIA 2024

作者： Ba, Yuanxiao Lanzhou Vocational Technical College Gansu Lanzhou China

ISBN: (纸本)9781510689053

The digital image of embroidery has complex edge structure and high repetition rate texture features. Post-processing such as region detection is a challenging task. A long embroidery image data set for learning and training is constructed. Based on the deep network and multi-scale detection structure, the lightweight detection network model GSEm-Net is introduced to detect the long embroidery pattern in real time. Experiments show that compared with yoloV8, the detection accuracy of this method is equivalent, and the detection speed is 1.5 times that of yoloV8, but the generated model is smaller, and it is easier to deploy to low-computing edge devices, which effectively improves the target detection efficiency. © 2025 SPIE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Research on distribution network reconstruction technology considering the time variability of distributed power sources 2

Research on distribution network reconstruction technology c...

引用

2nd international conference on Big Data, computational intelligence, and Applications, BDCIA 2024

作者： Yao, Ziqi Xu, Yan State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Baoding071003 China

ISBN: (纸本)9781510689053

A distribution network reconfiguration technique that takes into account the time-varying nature of distributed power sources is proposed for a high proportion of distributed power sources accessing the distribution network. Firstly, the theory of reconfiguration of distribution networks taking into account the access of distributed power sources is introduced, and the calculation method of the forward and backward generation of distribution network currents is proposed. Next, a long- and short-term memory neural network prediction model is developed to address the time-varying nature of distributed power output and load. In the study of distribution network reconfiguration problem, the particle swarm genetic algorithm is used to obtain the dynamic reconfiguration strategy of distribution network with the minimization of active power loss and the minimization of grid operation cost as the comprehensive objective function. Finally, the IEEE33 node is used as an example for validation, and the strategy effectively reduces the active power loss and operating cost of the distribution network, which is of great significance for the economic operation of the distribution network. © 2025 SPIE.

关键词： Particles Evolutionary algorithms neural networks Genetic algorithms Power grids Particle swarm optimization Photovoltaics Computer simulations Mathematical optimization Switches

来源：评论

学校读者我要写书评

暂无评论

The application of GIS technology in accident prevention and management in intelligent traffic management systems 2

The application of GIS technology in accident prevention and...

引用

2nd international conference on Big Data, computational intelligence, and Applications, BDCIA 2024

作者： Yu, Xintong Shenzhen University Shenzhen China

ISBN: (纸本)9781510689053

This study investigates the integration of Geographic Information System (GIS) technology with Intelligent Traffic Management Systems (ITMS) for accident prevention and management, addressing the limitations of traditional systems in processing real-time data and spatial analysis. The research implements a comprehensive GIS-based framework combining distributed computing, machine learning algorithms, and WebGIS technologies. The system architecture incorporates improved Hidden Markov Models for GPS trajectory mapping, Graph neural networks for traffic flow prediction, and enhanced Ordering Points to Identify the Clustering Structure (OPTICS) algorithms for spatial analysis. Experimental results demonstrate significant improvements in system performance, with the accident prevention model achieving 89.7% accuracy and an AUC value of 0.94. The accident response time was reduced by 42%, from 15 minutes to 8.7 minutes, while the secondary accident rate decreased from 7.2% to 3.1%. The system successfully handled peak concurrent users of 10 million with 99.9% of requests responding within 200 milliseconds, leading to a 12.3% reduction in average commuting time and 24.6% decrease in congestion duration. This study confirms that the integration of GIS technology with intelligent traffic management systems significantly enhances traffic safety and efficiency while providing valuable insights for future smart city initiatives. © 2025 SPIE.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

The Symphony of Style: An Extensive Examination of Determination Mechanisms in Deep Learning-Inspired Outfit Suggestions 2

The Symphony of Style: An Extensive Examination of Determina...

引用

2nd international conference on computational intelligence, Communication Technology and Networking, CICTN 2025

作者： Guru Prasad, M.S. Bhosagi, Ravatappa A. Madhusudhana, K. Prithviraj Chandrappa, S. Kumar, Vikash Dehradun India School of Computing and Information Technology Reva University Bengaluru India Dept. of Electronics & Communication Engineering SDM Institute of Technology Ujire India NMAMIT Mangalore India Bengaluru India Department of Computer Application Graphic Era Deemed University Dehradun India

ISBN: (纸本)9798331530389

In the field of the fashion industry, the introduction of deep learning technology has taken an innovative revolution by providing assistance in the construction of intellectual systems that are intelligent to deliver personalized ensemble recommendations. In this research work, an innovative ensemble recommendation structure called Deep Learning VGG16 (Visual Geometry Group 16) recommender is presented. The proposed method allows a deep learning model VGG16 to understand complex patterns and developments resulting from a vast group of fashion images. In order to increase the user experience and greater participation in the well-established fashion industry, the system offers personalized ensemble ideas. The important, core and fundamental component of the system is VGG16, consisting of 13 convolutional layers and 3 fully connected layers, which is used to support the analysis of fashion images. A cutting-edge convolutional neural network (CNN) model is improved over a large and diverse collection of fashion images. Model will extract advanced high-level information and statistics with the capability to distinguish particulars in colour patterns, clothing combinations, and stylistic elements. Using this process of development, the system becomes better at identifying user preferences and fashion trends. © 2025 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Exploration of face recognition technology based on the improved LeNet-5 neural network 2

Exploration of face recognition technology based on the impr...

引用

2nd international conference on Big Data, computational intelligence, and Applications, BDCIA 2024

作者： Lin, Aiqin Liaoning Vocational and Technical College of Economics Liaoning Shenyang110122 China

ISBN: (纸本)9781510689053

The LeNet-5 convolutional neural network is an algorithm for identifying image feature information, which has achieved excellent recognition performance on handwritten digit datasets. However, its recognition rate is relatively low for facial expression recognition. To better recognize the complex facial expression data, the LeNet-5 convolutional neural network was improved by adopting a shallow convolutional structure and consecutively applying 1×1 and 3×3 convolutional layers. After each convolutional layer, Z-score normalization was applied. To enhance computation speed, the well-performing Relu activation function was selected to reduce the vanishing gradient problem. The softmax function was employed in the output layer to calculate the probabilities of facial expression images. Simulation results indicate that the proposed optimization algorithm achieved an accuracy of 99.2% on the validation set, improving by 2.78% compared to the traditional LeNet-5 model. Compared with other optimization algorithms for facial expression recognition, the improved LeNet-5 algorithm demonstrates higher accuracy and efficiency, further validating the superiority of the improved LeNet-5 algorithm. © 2025 SPIE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Research on evaluating English teaching quality using the PSO-BP algorithm 2

Research on evaluating English teaching quality using the PS...

引用

2nd international conference on Big Data, computational intelligence, and Applications, BDCIA 2024

作者： Li, Dongmei Jiang, Xu School of International Education Heilongjiang University of Technology Jixi China

ISBN: (纸本)9781510689053

This paper proposes a model that integrates Particle Swarm Optimization (PSO) with the Backpropagation (BP) neural network to achieve efficient evaluation of English teaching quality. Traditional BP neural networks often struggle with issues like slow convergence and susceptibility to local minima, especially when processing complex, multi-dimensional educational data. By leveraging PSO's global search capability, this model effectively optimizes the BP network's initial weights and thresholds, addressing these limitations and enhancing both training efficiency and prediction accuracy. This paper utilizes data from a university English teaching program to validate the PSO-BP model's performance. Experimental results demonstrate that the PSO-BP model achieves higher accuracy and stability in evaluating teaching quality compared to the standard BP algorithm. The model's enhanced convergence speed and improved stability allow it to handle complex teaching quality metrics with greater precision while significantly reducing training time. © 2025 SPIE.

关键词： Particle swarm optimization (PSO)

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358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：