检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Taylor, Christina G. Chan, Jesse Oden Institute for Computational Science and Engineering University of Texas at Austin United States Department of Computational Applied Mathematics and Operations Research Rice University United States

High-order entropy stable summation-by-parts (SBP) schemes are a class of robust and accurate numerical methods for hyperbolic conservation laws that are numerically stable at arbitrary order without the need for artificial stabilization. While SBP schemes are well-established on simplicial and tensor-product elements, they have not been extended to cut meshes. Cut meshes provide a convenient and efficient means of mesh generation for domains with embedded boundaries but can be difficult to use due to their arbitrarily shaped cut elements. Using the skew-hybridized SBP formulation of Chan [1], we present a high-order accurate, entropy stable scheme for hyperbolic conservation laws on cut meshes. The formulation requires positive/non-negative weight quadrature rules on cut elements, which we construct via explicit parameterizations, subtriangulations, and Carathéodory pruning. We numerically verify the accuracy and stability of our method using the shallow water and compressible Euler equations and note promising results for the use of state redistribution with entropy stable methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Euler equations

来源：评论

学校读者我要写书评

暂无评论

THREE-PRECISION ITERATIVE REFINEMENT WITH PARAMETER REGULARIZATION AND PREDICTION FOR SOLVING LARGE SPARSE LINEAR SYSTEMS

arXiv

引用

arXiv 2025年

作者： Ge, Jifeng Zhang, Juan Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Hunan KeyLaboratory for Computation and Simulation in Science and Engineering School of Mathematics and Computational Science Xiangtan University Hunan Xiangtan411105 China

This study presents a novel mixed-precision iterative refinement algorithm, GADI-IR, within the general alternating-direction implicit (GADI) framework, designed for efficiently solving large-scale sparse linear systems. By employing low-precision arithmetic, particularly half-precision (FP16), for computationally intensive inner iterations, the method achieves substantial acceleration while maintaining high numerical accuracy. Key challenges such as overflow in half-precision and convergence issues for low precision are addressed through careful backward error analysis and the application of a regularization parameter α. Furthermore, the integration of low-precision arithmetic into the parameter prediction process, using Gaussian Process Regression (GPR), significantly reduces computational time without degrading performance. The method is particularly effective for large-scale linear systems arising from discretized partial differential equations and other high-dimensional problems, where both accuracy and efficiency are critical. Numerical experiments demonstrate that the use of mixed-precision strategies not only accelerates computation but also ensures robust convergence, making the approach advantageous for various applications. The results highlight the potential of leveraging lower-precision arithmetic to achieve superior computational efficiency in high-performance computing. © 2025, CC BY.

关键词： Convergence of numerical methods

来源：评论

学校读者我要写书评

暂无评论

SPARSE RECOVERY OF ELLIPTIC SOLVERS FROM MATRIX-VECTOR PRODUCTS

引用

SIAM Journal on Scientific computing 2024年第2期46卷 A998-A1025页

作者： Schäfer, Florian Owhadi, Houman Computational Science and Engineering Georgia Institute of Technology AtlantaGA30332 United States Department of Computing + Mathematical Sciences California Institute of Technology PasadenaCA91125 United States

In this work, we show that solvers of elliptic boundary value problems in d dimensions can be approximated to accuracy ϵ from only (log(N) logd(N/ϵ)) matrix-vector products with carefully chosen vectors (right-hand sides). The solver is only accessed as a black box, and the underlying operator may be unknown and of an arbitrarily high order. Our algorithm (1) has complexity (N log2(N) log2d(N/ϵ)) and represents the solution operator as a sparse Cholesky factorization with (N log(N) logd(N/ϵ)) nonzero entries, (2) allows for embarrassingly parallel evaluation of the solution operator and the computation of its log-determinant, (3) allows for (log(N) logd(N/ϵ)) complexity computation of individual entries of the matrix representation of the solver that, in turn, enables its recompression to an (N logd(N/ϵ)) complexity representation. As a byproduct, our compression scheme produces a homogenized solution operator with near-optimal approximation accuracy. By polynomial approximation, we can also approximate the continuous Green's function (in operator and Hilbert-Schmidt norm) to accuracy ϵ from (log1+d(ϵ 1)) solutions of the PDE. We include rigorous proofs of these results. To the best of our knowledge, our algorithm achieves the best known trade-off between accuracy ϵ and the number of required matrix-vector products. © 2024 Society for Industrial and Applied mathematics Publications. All rights reserved.

关键词： Principal component analysis

来源：评论

学校读者我要写书评

暂无评论

Optimal control of alcoholism spreading through awareness over multiplex network

引用

International Journal of Biomathematics 2021年第6期14卷 33-58页

作者： Padmavathi Ramamoorthi Senthil Kumar Muthukrishnan Department of Science and Humanities Info Institute of Engineering CoimbatoreIndia Department of Applied Mathematics and Computational Sciences PSG College of Technology CoimbatoreIndia

This paper proposes the SISRS epidemic model to represent alcohol addiction among *** spreading of alcohol addiction is controlled by creating awareness among the people and also by treating them to overcome *** network is used to study the dynamics of *** spreads over the physical contact layer and follows the SISRS process whereas human awareness spreads over the virtual contact layer and follows the UAU *** on the Microscopic Markov Chain Approach competing dynamics of spreading of alcohol addiction and human awareness diffusion are *** conditions for the existence of an alcohol-free population are *** optimal control problem using a suitable cost index is formulated to reduce the alcohol addicts and the optimal control strategy using Pontryagin’s Minimum Principle is *** results are developed to find the effect of various parameters and to analyze the effects of different control *** results obtained from this model are closer to the data collected in the National Survey of Drug Use and Health(NSDUH)from 2002 to 2018.

关键词： Alcohol spreading information diffusion Microscopic Markov Chain Approach optimal control

来源：评论

学校读者我要写书评

暂无评论

Helmholtz decomposition based windowed Green function methods for elastic scattering problems on a half-space

arXiv

引用

arXiv 2023年

作者： Yin, Tao Zhang, Lu Zheng, Weiying Zhu, Xiaopeng LSEC Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Mathematical Sciences Zhejiang University Hangzhou310027 China LSEC NCMIS Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and System Sciences Chinese Academy of Sciences Beijing100190 China School of Mathematical Science University of Chinese Academy of Sciences Beijing100049 China

This paper proposes a new Helmholtz decomposition based windowed Green function (HD-WGF) method for solving the time-harmonic elastic scattering problems on a half-space with Dirichlet boundary conditions in both 2D and 3D. The Helmholtz decomposition is applied to separate the pressure and shear waves, which satisfy the Helmholtz and Helmholtz/Maxwell equations, respectively, and the corresponding boundary integral equations of type (I + T) = f, that couple these two waves on the unbounded surface, are derived based on the free-space fundamental solution of Helmholtz equation. This approach avoids the treatment of the complex elastic displacement tensor and traction operator that involved in the classical integral equation method for elastic problems. Then a smooth "slow-rise" windowing function is introduced to truncate the boundary integral equations and a "correction" strategy is proposed to ensure the uniformly fast convergence for all incident angles of plane incidence. Numerical experiments for both two and three dimensional problems are presented to demonstrate the accuracy and efficiency of the proposed method. Copyright © 2023, The Authors. All rights reserved.

关键词： Boundary integral equations

来源：评论

学校读者我要写书评

暂无评论

Optimized Predictive Storage Resource Allocation Through Neural Forecasting for Cloud Environments

Optimized Predictive Storage Resource Allocation Through Neu...

引用

2024 International Conference on Innovative computing, Intelligent Communication and Smart Electrical Systems, ICSES 2024

作者： Sridevi Ponmalar, P. Adithya Pothan Raj, V. Jebaseelan, S. D. Sundarsingh Phade, Gayatri Srithar, V. Harikrishnan, R. School of computing Srm Institute of Science and Technology Department of Computational Intelligence Kattankulathur Campus Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Dept. of Cse Chennai India Sathyabama Institute of Science and Technology Dept of Eee Chennai119 India Sandip Institute of Technology & Research Centre Nashik India PeriyarManiammai Institute of Science & Technology Department of Computer Applications Thanjavur India Symbiosis Institute of Technology Symbiosis International Deemed University Pune Campus Pune412115 India

ISBN: (纸本)9798331543617

The demand for efficient and scalable management of storage resources is growing enormously with the rapid growth in data-intensive applications within the cloud environment. Optimized PSRANF is the state-of-the-art approach towards dynamic storage resource allocation, based on the forecast of future demands in storage. PSRANF utilizes state-of-the-art neural forecasting with Long Short-Term Memory (LSTM) networks and Transformer designs to analyze the pattern of historical storage usage for highly accurate future need predictions. By proactively adjusting storage capacity to these predictions, PSRANF strikes an optimal balance between performance and cost by reserving just-in-time resources. It ensures that there is no risk of over-provisioning, which would be too costly. In the same breath, the risk of under-provisioning, which leads to performance bottlenecks, is avoided. What is more, the system will apply prioritization, placing the data of higher priority or frequently accessed data into faster storage tiers of a higher class of performance and less important classes of data into cost-effective storage. The adaptive feedback loop continuously refines the forecasting model, which, over time, improves accuracy and allows the system to handle changes in workload patterns. PSRANF combines neural forecasting with resource allocation in such a way that is cost-effective;thus, it is very well placed for cloud environments where the demand for storage is dynamic in nature and requires intelligent data-driven approaches. The AWS implementation of PSRANF has turned out to be quite a helpful tool in optimizing the storage resource allocation process. While it is able to predict 98.5% of the storage needs correctly by achieving a cost saving of up to 18.7%, managing data from 97.8% to 99.2%, and resources from 95.4%, it's robust for improvements in cloud storage management and operational efficiency. © 2024 IEEE.

关键词： Storage efficiency

来源：评论

学校读者我要写书评

暂无评论

Using Data Mining Techniques to Analyze Facial Expression Motion Vectors 6th

Using Data Mining Techniques to Analyze Facial Expression Mo...

引用

6th International Conference on Dynamics of Information Systems, DIS 2023

作者： Roshanzamir, Mohamad Alizadehsani, Roohallah Roshanzamir, Mahdi Shoeibi, Afshin Gorriz, Juan M. Khosravi, Abbas Nahavandi, Saeid Acharya, U. Rajendra Department of Computer Engineering Faculty of Engineering Fasa University Fasa74617-81189 Iran Deakin University GeelongVIC Australia Department of Electrical and Computer Engineering University of Tabriz Tabriz Iran Data Science and Computational Intelligence Institute University of Granada Granada Spain Department of Signal Theory Networking and Communications Universidad de Granada Granada Spain Swinburne University of Technology HawthornVIC3122 Australia School of Mathematics Physics and Computing University of Southern Queensland Springfield Australia

ISBN: (纸本)9783031503191

Automatic recognition of facial expressions is a common problem in human-computer interaction. While humans can recognize facial expressions very easily, machines cannot do it as easily as humans. Analyzing facial changes during facial expressions is one of the methods used for this purpose by the machines. In this research, facial deformation caused by facial expressions is considered for automatic facial expression recognition by machines. To achieve this goal, the motion vectors of facial deformations are captured during facial expression using an optical flow algorithm. These motion vectors are then used to analyze facial expressions using some data mining algorithms. This analysis not only determined how changes in the face occur during facial expressions but can also be used for facial expression recognition. The facial expressions investigated in this research are happiness, sadness, surprise, fear, anger, and disgust. According to our research, these facial expressions were classified into 12 classes of facial motion vectors. We applied our proposed analysis mechanism to the extended Cohen-Kanade facial expression dataset. Our developed automatic facial expression system achieved 95.3%, 92.8%, and 90.2% accuracy using Deep Learning (DL), Support Vector Machine (SVM), and C5.0 classifiers, respectively. In addition, based on this research, it was determined which parts of the face have a greater impact on facial expression recognition. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Data mining

来源：评论

学校读者我要写书评

暂无评论

Scattering for 3D Cubic Focusing NLS on the Domain Outside a Convex Obstacle Revisited

引用

Acta Mathematica Sinica,English Series 2022年第6期38卷 1054-1068页

作者： Cheng Bin XU Teng Fei ZHAO Ji Qiang ZHENG The Graduate School of China Academy of Engineering Physics Beijing 100088P.R.China School of Mathematics and Physics University of Science and Technology BeijingBeijing 100083P.R.China Institute of Applied Physics and Computational Mathematics P.O.Box 8009Beijing 100088P.R.China

In this article,we consider the focusing cubic nonlinear Schr?dinger equation(NLS)in the exterior domain outside of a convex obstacle in R3with Dirichlet boundary *** revisit the scattering result below ground state in Killip-Visan-Zhang[The focusing cubic NLS on exterior domains in three ***,1,146-180(2016)]by utilizing the method of Dodson and Murphy[A new proof of scattering below the ground state for the 3d radial focusing cubic ***.,145,4859-4867(2017)]and the dispersive estimate in Ivanovici and Lebeau[Dispersion for the wave and the Schr?dinger equations outside strictly convex obstacles and ***.,355,774-779(2017)],which avoids using the concentration *** conquer the difficulty of the boundary in the focusing case by establishing a local smoothing effect of the *** on this effect and the interaction Morawetz estimates,we prove that the solution decays at a large time interval,which meets the scattering criterion.

关键词： Schrodinger equation exterior domain global well-posedness scattering criterion

来源：评论

学校读者我要写书评

暂无评论

Interactive Multi-Persona Analysis for a CollaboraTive Framework Using Large Language Models (IMPACTFUL): A Case Study of South Korea's National Assembly

Interactive Multi-Persona Analysis for a CollaboraTive Frame...

引用

International Conference on Information and Communication Technology Convergence (ICTC)

作者： Jeeseun Baik Won-Yong Shin Sounman Hong School of Public Policy and Management Yonsei University Seoul Republic of Korea School of Mathematics and Computing (Computational Science and Engineering) Yonsei University Seoul Republic of Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

This study investigates how the large language models (LLMs) can improve collective decision-making activities, specifically within the legislative processes of South Korea's National Assembly. By employing LLMs to assimilate and analyze input from multiple stakeholders' legislative decision-making, this approach increases both transparency and the public's grasp of legislative operations. We introduce an innovative multi-persona collaborative framework that highlights the role of LLMs in enhancing understanding of legislative decisions and paves the way for their broader implementation in various social-scientific contexts.

关键词： Analytical models Large language models Decision making Collaboration Information and communication technology Stakeholders Assembly Convergence

来源：评论

学校读者我要写书评

暂无评论

Uncertainty quantification in groundwater volume predictions from seismic data using neural networks 30

Uncertainty quantification in groundwater volume predictions...

引用

30th European Meeting of Environmental and engineering Geophysics, Held at the Near Surface Geoscience Conference and Exhibition 2024, NSG 2024

作者： Khalili, M. Göransson, P. Hesthaven, J.S. Heinonen, S. Pasanen, A. Vauhkonen, M. Lähivaara, T. Department of Technical Physics University of Eastern Finland Finland Department of Aeronautical and Vehicle Engineering KTH Royal Institute of Technology Stockholm Sweden Computational Mathematics and Simulation Science Ecole Polytechnique Federale de Lausanne Lausanne Switzerland Institute of Seismology University of Helsinki Finland Geological Survey of Finland Finland

ISBN: (纸本)9789462825055

Optimum groundwater management is important for addressing the global challenges of water scarcity, especially in arid regions. This study demonstrates the application of synthetic data combined with seismic methods to quantify water volumes in a controlled sand pool environment, mimicking a subsurface aquifer. Utilizing seismic simulations, we employ the nodal discontinuous Galerkin method to generate data reflecting the propagation of seismic waves through a three-dimensional poroviscoelastic-viscoelastic medium. These data are then analyzed using fully connected neural networks optimized through hyperparameter tuning to predict the water volume from seismic signatures accurately. The approach incorporates Deep Evidential Regression, which quantifies two main types of uncertainties: aleatoric, resulting from measurement errors, and epistemic, resulting from inadequate model knowledge. This dual uncertainty quantification enhances the reliability and interpretability of the water volume predictions, providing a robust framework for groundwater monitoring. Our results indicate that the aleatoric uncertainties are nearly consistent but, epistemic uncertainties are large for higher values of water volume suggesting the possibility of adding more data for model improvement. © 30th European Meeting of Environmental and engineering Geophysics, Held at the Near Surface Geoscience Conference and Exhibition 2024, NSG 2024.

关键词： Seismic response

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：