检索结果-内蒙古大学图书馆

2021 3rd International Conference on Artificial Intelligence and Computer science, AICS 2021

作者： Hu, Siquan Huang, Zhao Shi, Zhiguo School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Shunde Graduate School University of Science and Technology Beijing Foshan China Beijing Big Data Center Beijing China

For intelligent control of network traffic, to solve the problem of low utilization of public network bandwidth, we put forward scheduling data flow between data center based on SDN technology. First, we connect the data center distributed in different locations by wide area network and exchange or share the research data of high performance. Then, the system can sense the utilization and performance of the network bandwidth resources between the data center. Based on the results of perception, we can dynamically adjust and optimize the path of data and maximize the utilization of network link. SDN is a new software based network structure. This paper uses SDN network architecture to schedule the traffic of data center, and constructs a two-layer network suitable for cloud computing and virtualization environment. It realizes the global, dynamic and intelligent data flow. © Journal of Physics: Conference Series 2021.

关键词： Wide area networks

来源：评论

学校读者我要写书评

暂无评论

An extension of spectral Mantel's theorem on wheels

引用

Discrete Mathematics 2025年第11期348卷

作者： Li, Rui Liu, Bo Zhai, Mingqing School of Mathematics Hohai University Jiangsu Nanjing 211100 China School of Mathematics and Big Data Anhui University of Science and Technology Anhui Huainan 232001 China School of Mathematics and Statistics Nanjing University of Science and Technology Jiangsu Nanjing 210094 China

A graph is considered wheel-free if the neighborhood of any vertex is acyclic. The extremal problems associated with wheel-free graphs have a long-standing history of research. In 1983, Gallai and Zelinka independently posed the question of determining the maximum number of triangles in an n-vertex wheel-free graph. Moving forward to 2021, Zhao, Huang and Lin investigated the maximum spectral radius of graphs within the same family of wheel-free graphs. In this paper, we focus on graphs of fixed size that do not contain isolated vertices. In 1970, Nosal established that every graph G with m edges and a spectral radius ρ(G)>m contains at least one triangle. This result is known as the spectral Mantel's theorem. Nikiforov further refined this theorem by showing that any graph G with m edges and a spectral radius ρ(G)≥m contains a triangle, except when G is a complete bipartite graph. In this work, we present an extension of spectral Mantel's theorem, which asserts that every graph G with m≥25 edges and a spectral radius [Formula presented] contains a wheel, unless G is a book (possibly missing an edge). © 2025 Elsevier B.V.

关键词： Mantel's theorem Spectral radius Triangle Wheel

来源：评论

学校读者我要写书评

暂无评论

Optimizing Takagi-Sugeno Fuzzy Models For Improving Leak Detection in Water Distribution Networks

Optimizing Takagi-Sugeno Fuzzy Models For Improving Leak Det...

引用

Computational Intelligence for Energy, Transport and Environmental Sustainability (CIETES), IEEE Symposia on

作者： Qusai Khaled Uzay Kaymak Laura Genga Jheronimus Academy of Data Science Eindhoven University of Technology Eindhoven The Netherlands School of Industrial Engineering Eindhoven University of Technology Eindhoven The Netherlands

ISBN: (数字)9798331508258

ISBN: (纸本)9798331508265

Leakage detection in water distribution networks (WDNs) is critical for reducing water loss and ensuring operational efficiency. While machine learning methods are often applied, they can lack interpretability. Takagi-Sugeno (Tsk) fuzzy systems offer a balance between accuracy and interpretability but are prone to overfitting and incur high computational costs, especially with large datasets. To address these issues, we explore various optimization and regularization techniques to improve Tsk performance. The models were trained on a large-scale benchmark dataset containing 1000 leak scenarios, each a year-long time series at half-hour intervals, totaling over 17 million data points. A systematic preprocessing pipeline was applied, including time-series segmentation, mutual information-based feature selection, and class imbalance handling. Alongside the baseline training of Adaptive Neuro-Fuzzy Inference Systems (ANFIS) using gradient descent (GD), we also trained Tsk models using stochastic gradient descent (SGD) and mini-batch gradient descent (MBGD). State-of-the-art regularization techniques such as uniform regularization and rule dropout were also incorporated to prevent overfitting. Key results show that SGD and MBGD models outperformed GD models in leak detection rates and achieved significantly lower false alarm rates than traditional machine learning models. These findings underscore the potential of fuzzy systems for effective leak detection, provided that appropriate learning and regularization techniques are employed.

关键词： Training Adaptation models Computational modeling Time series analysis Machine learning Distribution networks Takagi-Sugeno model Leak detection Fuzzy systems Overfitting

来源：评论

学校读者我要写书评

暂无评论

A Novel Gold Futures Price Prediction Model based on PCA-AGRU 29

A Novel Gold Futures Price Prediction Model based on PCA-AGR...

引用

29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Wang, Jingyang Lu, Tong Liu, Jindian Sun, Qiuhong Qi, Lianyong Zhou, Xiaokang Hebei University of Science and Technology School of Information Science and Engineering Shijiazhuang China Shiga University Faculty of Data Science Hikone522-8522 Japan Qingdao China RIKEN Center for Advanced Intelligence Project RIKEN Tokyo103-0027 Japan

ISBN: (纸本)9798350330717

As an important financial investment commodity, the price fluctuations of gold significantly impact the global economy and the stability of the financial market. Therefore, it is of great significance to accurately predict the price of gold futures. This paper presents a novel gold futures price prediction model, PCA-AGRU, based on Principal Component Analysis (PCA) and Adaptive Gated Recurrent Unit (AGRU). PCA is utilized for the dimensionality reduction of data while extracting essential features. AGRU bases on Gated Recurrent Unit (GRU), embeds Self-Attention (SA), and adds an adaptive adjustment mechanism, making the model more effective in capturing long-term dependencies within time series data. This paper uses the international gold futures market data as the experimental dataset, and uses Maximal Information Coefficient (MIC) to analyze the correlation of the influencing factors. The PCA-AGRU model is compared with five prediction models of GRU, SA-GRU, AGRU, PCA-GRU, and PCA-SA-GRU. The experimental results show that the PCA-AGRU model performs best in forecasting gold futures prices. © 2023 IEEE.

关键词： AGRU deep learning Gold Futures PCA Price Prediction SA

来源：评论

学校读者我要写书评

暂无评论

Explaining Grover's Quantum Algorithm to College Students

Explaining Grover's Quantum Algorithm to College Students

引用

Computer science, Computer Engineering, & Applied Computing (CSCE), Congress in

作者： Leonidas Deligiannidis School of Computing and Data Science Wentworth Institute of Technology Boston MA USA

Wentworth Institute of technology is a baccalaureate degree granting institution and in recent years we have also developed several Master's programs. Our department offers several degrees leading to a Bachelor of science in Computer science, Computer Networking, Information technology, Cybersecurity, and data science. All our programs are designed to be hands-on and expose students to a wide skill set. All our majors need to take several security-related courses. One of the latest security related courses we developed is in Quantum Computing with a focus on security. Quantum Computing is a groundbreaking technology that exploits the laws and properties of quantum mechanics. It can dramatically speed up computations of certain problems and surpass the computation power of modern supercomputers. One notable quantum algorithm we cover in our newly developed course is Grover's algorithm. It is used to search an unstructured database while providing quadratic speedup, compared to its classical counterpart. While demonstrating Grover's algorithm in the classroom, the students raise many questions and explaining all the details of the algorithm is challenging. In this paper, we explain and illustrate the theoretical and implementational challenges and provide examples and solutions.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Dynamic Interval Multi-Objective Evolutionary Algorithm Based on Multi-Task Learning and Inverse Mapping

引用

IEEE Transactions on Evolutionary Computation 2025年

作者： Wang, Feimeng Sun, Jing Gan, Xingjia Gong, Dunwei Wang, Gaige Guo, Yongde Qingdao University of Science and Technology College of Automation and Electronic Engineering Qingdao Shandong266061 China Qingdao University of Science and Technology School of Data Science Qingdao Shandong266061 China Central South University School of Automation Changsha Hunan410083 China Ocean University of China Department of Computer Science and Technology Qingdao Shandong266071 China City University of Macau Faculty of Data Science Macau999078 China

Dynamic interval multi-objective optimization problems, such as those encountered in wireless sensor network scheduling and portfolio selection, are increasingly prevalent. However, they present significant challenges due to the inherent uncertainty and variability of their parameters. This paper proposes a dynamic interval multi-objective evolutionary algorithm in terms of multi-task learning and inverse mapping. The algorithm employs an interval-based MOEA/D as its foundational framework. Upon encountering environmental changes, prediction models for the midpoints and widths of intervals are developed using multi-task learning combined with a self-evolving fuzzy system. These models generate a predicted Pareto front (PF) in the objective space. Subsequently, inverse mappings of the objective functions at the new time are established to identify solutions that correspond to the predicted PF in the decision space. Finally, these solutions are expanded to form an initial population at the new time. Testing on eighteen benchmark optimization problems and an uncertain scheduling of underwater wireless sensor networks, the proposed algorithm demonstrates both competitiveness and superiority when compared to five state-of-the-art algorithms. © 1997-2012 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Image Orientation Estimation Based On Deep Learning - A Survey

引用

Procedia Computer science 2024年 242卷 1193-1197页

作者： Ruijie Xu Yong Shi Zhiquan Qi Research Center on Fictitious Economy and Data Science University of Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Big Data Mining and Knowledge Management University of Chinese Academy of Sciences Beijing 00190 China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing 101408 China School of Economics and Management University of Chinese Academy of Sciences Beijing 100190 China College of Information Science and Technology University of Nebraska Omaha 68182 USA

In the realm of visual tasks, the estimation of orientation plays a pivotal role yet often remains an understudied aspect in the gamut of image analysis research. This paper endeavors to address this deficiency by conducting a comprehensive review of methods for orientation estimation within 2D imaging contexts. We aim to provide researchers with an exhaustive overview and detailed analysis of the techniques utilized for orientation estimation, thereby enhancing their understanding of this complex field. We introduce an organized classification of orientation estimation methods, segmented into approaches based on classification algorithms and those based on regression models. This classification not only sheds light on the distinct methodologies but also scrutinizes their underlying assumptions, practical applications. Additionally, the study identifies and underscores emerging research opportunities that hold the potential to enrich the discourse and technical advancements in orientation estimation, thereby encouraging deeper academic investigation and technological development.

关键词： Classification-based Orientation Estimation Regression-based Orientation Estimation

来源：评论

学校读者我要写书评

暂无评论

MMAL: Multi-Modal Analytic Learning for Exemplar-Free Audio-Visual Class Incremental Tasks 24

MMAL: Multi-Modal Analytic Learning for Exemplar-Free Audio-...

引用

32nd ACM International Conference on Multimedia, MM 2024

作者： Yue, Xianghu Zhang, Xueyi Chen, Yiming Zhang, Chengwei Lao, Mingrui Zhuang, Huiping Qian, Xinyuan Li, Haizhou Department of Electrical and Computer and Engineering National University of Singapore Singapore Laboratory for Big Data and Decision National University of Defense Technology Hunan Changsha China School of Electronic Electrical and Communication Engineering University of the Chinese Academy of Sciences Beijing China National Key Laboratory of Information Systems Engineering National University of Defense Technology Hunan Changsha China Shien-Ming Wu School of Intelligent Engineering South China University of Technology Guangdong Guangzhou China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Shenzhen China

ISBN: (纸本)9798400706868

Class-incremental learning poses a significant challenge under an exemplar-free constraint, leading to catastrophic forgetting and sub-par incremental accuracy. Previous attempts have focused primarily on single-modality tasks, such as image classification or audio event classification. However, in the context of Audio-Visual Class-Incremental Learning (AVCIL), the effective integration and utilization of heterogeneous modalities, with their complementary and enhancing characteristics, remains largely unexplored. To bridge this gap, we propose the Multi-Modal Analytic Learning (MMAL) framework, an exemplar-free solution for AVCIL that employs a closed-form, linear approach. To be specific, MMAL introduces a modality fusion module that re-formulates the AVCIL problem through a Recursive Least-Square (RLS) perspective. Complementing this, a Modality-Specific Knowledge Compensation (MSKC) module is designed to further alleviate the under-fitting limitation intrinsic to analytic learning by harnessing individual knowledge from audio and visual modality in tandem. Comprehensive experimental comparisons with existing methods show that our proposed MMAL demonstrates superior performance with the accuracy of 76.71%, 78.98%, and 76.19% on AVE, Kinetics-Sounds, and VGGSounds100 datasets, respectively, setting new state-of-the-art AVCIL performance. Notably, compared to those memory-based methods, our MMAL, being an exemplar-free approach, provides good data privacy and can better leverage multi-modal information for improved incremental accuracy. © 2024 ACM.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Stacked Mosaic Detection based on Line Expansion

Stacked Mosaic Detection based on Line Expansion

引用

Intelligent Media, big data and Knowledge Mining (IMBDKM), International Conference on

作者： Zhongfei Xu Yan Fu Aixiang Cui Big Data Research Center University of Electronic Science and Technology of China Chengdu P. R. China Chengdu Union Big Data Tech. Inc. Chengdu P. R. China

When uploading multimedia data such as photos or videos on network, they might be covered with mosaic blocks since some private information is not suitable for exposing. In some situation, mosaic images or video frames need to be restored or trimmed from them, it is necessary to detect the mosaic so as to discriminate these data for subsequent processing. Up to now, most mosaic detection methods are based on edge detection. However, mosaic regions with similar colors may cause several similar mosaic blocks to be stacked together, which makes it difficult to extract sufficient edge features, and lead to hardly detecting the subsequent mosaic region. In this paper, a line expansion- based mosaic detection method is proposed. First, find the upper left point of a block, expand downward to obtain a vertical line. Second, expand to the right based on vertical line to get the whole rectangular block. Third, repeat above steps until the entire mosaic region is extracted, ignoring the regions that have been marked during extraction. The proposed method is compared with several representative methods under different sizes and stacked mosaic. The experimental results show that the proposed method outperforms the state-of-the-art methods on stacked mosaic.

关键词：

来源：评论

学校读者我要写书评

暂无评论

MedLogic-AQA: Enhancing Medical Question Answering with Abstractive Models Focusing on Logical Structures

arXiv

引用

arXiv 2024年

作者： Zafar, Aizan Mishra, Kshitij Ekbal, Asif Department of Computer Science and Engineering Indian Institute of Technology Patna India School of AI and Data Science Indian Institute of Technology Jodhpur India

In Medical question-answering (QA) tasks, the need for effective systems is pivotal in delivering accurate responses to intricate medical queries. However, existing approaches often struggle to grasp the intricate logical structures and relationships inherent in medical contexts, thus limiting their capacity to furnish precise and nuanced answers. In this work, we address this gap by proposing a novel Abstractive QA system MEDLOGIC-AQA that harnesses First Order Logic (FOL) based rules extracted from both context and questions to generate well-grounded answers. Through initial experimentation, we identified six pertinent first-order logical rules, which were then used to train a Logic-Understanding (LU) model capable of generating logical triples for a given context, question, and answer. These logic triples are then integrated into the training of MEDLOGIC-AQA, enabling effective and coherent reasoning during answer generation. This distinctive fusion of logical reasoning with abstractive QA equips our system to produce answers that are logically sound, relevant, and engaging. Evaluation with respect to both automated and human-based demonstrates the robustness of MEDLOGIC-AQA against strong baselines. Through empirical assessments and case studies, we validate the efficacy of MEDLOGIC-AQA in elevating the quality and comprehensiveness of answers in terms of reasoning as well as informativeness 1 © 2024, CC BY.

关键词：

来源：评论

学校读者我要写书评

暂无评论

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：

请选择收藏分类：

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

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：