检索结果-内蒙古大学图书馆

Small dataset augmentation with radial basis function approximation for causal discovery using constraint-based method

引用

ETRI JOURNAL 2025年第1期47卷 90-101页

作者： Jung, Chan Young Jang, Yun Sejong Univ Comp Sci & Engn Convergence Engn Intelligent Drone Seoul South Korea

Causal analysis involves analysis and discovery. We consider causal discovery, which implies learning and discovering causal structures from available data, owing to the significance of interpreting causal relationships in various fields. Research on causal discovery has been primarily focused on constraint- and score-based interpretable methods rather than on methods based on complex deep learning models. However, identifying causal relationships in real-world datasets remains challenging. Numerous studies have been conducted using small datasets with established ground truths. Moreover, constraint-based methods are based on conditional independence tests. However, such tests have a lower statistical power when applied to small datasets. To solve the small sample size problem, we propose a model that generates a continuous function from available samples using radial basis function approximation. We address the problem by extracting data from the generated continuous function and evaluate the proposed method on both real and synthetic datasets generated by structural equation modeling. The proposed method outperforms constraint-based methods using only small datasets.

关键词： causal discovery conditional independence constraint-based method data augmentation radial basis function approximation

来源：评论

学校读者我要写书评

暂无评论

A modified lattice Boltzmann approach based on radial basis function approximation for the non-uniform rectangular mesh

引用

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS 2024年第11期96卷 1695-1714页

作者： Hu, X. Bergada, J. M. Li, D. Sang, W. M. An, B. Northwestern Polytech Univ Sch Aeronaut POB 114Youyi West Rd 127 Xian 710072 Peoples R China Univ Politecn Cataluna Dept Fluid Mech Barcelona Spain Chinese Flight Test Estab Yanliang Peoples R China Shaanxi Univ Team Numer Algorithm Innovat Youth Innovat Team Taiyuan Shaanxi Peoples R China

We have presented a novel lattice Boltzmann approach for the non-uniform rectangular mesh based on the radial basis function approximation (RBF-LBM). The non-uniform rectangular mesh is a good option for local grid refinement, especially for the wall boundaries and flow areas with intensive change of flow quantities. Which allows, the total number of grid cells to be reduced and so the computational cost, therefore improving the computational efficiency. But the grid structure of the non-uniform rectangular mesh is no longer applicable to the classic lattice Boltzmann method (CLBM), which is based on the famous BGK collision-streaming evolution. This is why the present study is inspired by the idea of the interpolation-supplemented LBM (ISLBM) methodology. The ISLBM algorithm is improved in the present manuscript and developed into a novel LBM approach through the radial basis function approximation instead of the Lagrangian interpolation scheme. The new approach is validated for both steady states and unsteady periodic solutions. The comparison between the radial basis function approximation and the Lagrangian interpolation is discussed. It is found that the novel approach has a good performance on computational accuracy and efficiency. Proving that the non-uniform rectangular mesh allows grid refinement while obtaining precise flow predictions. When compared with the classic lattice Boltzmann method, the convergence speed of the present RBF-LBM is highly accelerated. The modified algorithm is trustable for both steady and unsteady solutions. Numerical results have a good agreement with that of the classic LBM and are more accurate than that of the Lagrangian interpolation schemes. image

关键词： LBM non-uniform rectangular mesh radial basis function approximation steady and unsteady solutions

来源：评论

学校读者我要写书评

暂无评论

The use of direct inverse maps to solve material identification problems: pitfalls and solutions

引用

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION 2017年第2期55卷 613-632页

作者： Asaadi, Erfan Wilke, Daniel N. Heyns, P. Stephan Kok, Schalk Univ Pretoria Dept Mech & Aeronaut Engn Ctr Asset Integr Management Pretoria South Africa

Material parameter identification is a technique that is used to calibrate material models, often a precursor to perform an industrial analysis. Conventional material parameter identification methods estimate the material parameters for a material model by solving an optimisation problem. An alternative but lesser-known approach, called a direct inverse map, directly maps the measured response to the parameters of a material model. In this study we investigate the potential pitfalls of the well-known stochastic noise and lesser-known model errors when constructing direct inverse maps. We show how to address these problems, explaining in particular the importance of projecting the measured response onto the domain of the simulated responses before mapping it to the material parameters. This paper concludes by proposing partial least squares regression as an elegant and computationally efficient approach to address stochastic and systematic (model) errors. This paper also gives insight into the nature of the inverse problem under consideration.

关键词： Inverse problem Inverse mapping Material parameter identification Partial least squares regression Principal component analysis radial basis function approximation

来源：评论

学校读者我要写书评

暂无评论

radial basis function PSEUDO-SPECTRAL SOLUTION OF THE NON-DARCY MODEL IN A POROUS MEDIUM

引用

JOURNAL OF POROUS MEDIA 2017年第6期20卷 479-490页

作者： Pekmen, B. TED Univ Basic Sci Unit TR-06420 Ankara Turkey

In this study, the radial basis function pseudo-spectral (RBF-PS) method is applied for solving natural convective flow in a square cavity and in a curved pipe filled with a porous medium. RBF-PS constructs differentiation matrices by the coordinate matrix formed by radial distances using multiquadric radial basis function (MQ-RBF) root r(2) + c(2). The direct implementation of the problem and the cheap computational cost using the small number of grid points make the proposed method captivating. The governing dimensionless equations are solved in terms of stream function, vorticity, and temperature. The results are given for several values of Rayleigh (Ra) number, Darcy (Da) number, and porosity. epsilon(p) in terms of average Nusselt number, or streamlines, isotherms, and vorticity contours. Physically the decrease in Darcy number suppresses the heat transfer while the convective heat transfer becomes prominent with the increase in Ra, and in epsilon(p).

关键词： radial basis function approximation natural convection porous medium Brinkman-Forchheimer-extended Darcy model

来源：评论

学校读者我要写书评

暂无评论

radial basis function generated Finite Differences for option pricing problems

引用

COMPUTERS & MATHEMATICS WITH APPLICATIONS 2018年第4期75卷 1462-1481页

作者： Milovanovic, Slobodan von Sydow, Lina Uppsala Univ Dept Informat Technol Div Sci Comp SE-75105 Uppsala Sweden

In this paper we present a numerical method to price options based on radial basis function generated Finite Differences (RBF-FD) in space and the Backward Differentiation Formula of order 2 (BDF-2) in time. We use Gaussian RBFs that depend on a shape parameter epsilon. The choice of this parameter is crucial for the performance of the method. We chose e as const . h(-1) and we derive suitable values of the constant for different stencil sizes in 1D and 2D. This constant is independent of the problem parameters such as the volatilities of the underlying assets and the interest rate in the market. In the literature on option pricing with RBF-FD, a constant value of the shape parameter is used. We show that this always leads to ill-conditioning for decreasing h, whereas our proposed method avoids such ill-conditioning. We present numerical results for problems in 1D, 2D, and 3D demonstrating the useful features of our method such as discretization sparsity, flexibility in node placement, and easy dimensional extendability, which provide high computational efficiency and accuracy. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： RBF-FD Finite Differences radial basis function approximation PDEs Multi-asset option pricing High-dimensional problems

来源：评论

学校读者我要写书评

暂无评论

3D high-quality temperature-field reconstruction method in furnace based on acoustic tomography

引用

APPLIED THERMAL ENGINEERING 2020年 179卷 115693-115693页

作者： Kong, Qian Jiang, Genshan Liu, Yuechao Sun, Jianhao North China Elect Power Univ Baoding 071003 Peoples R China

Reconstructed 3D high-quality temperature distribution in furnace can provide important information to better control boiler operations and to optimize the combustion process. Acoustic travel-time tomography is considered to be a promising method that uses the dependence of sound speed on temperature to reconstruct the temperature field. In this paper, a new 3D temperature field reconstruction method based on radial basis function approximation with polynomial reproduction (RBF-PR) and truncated generalized singular value decomposition (TGSVD) is proposed to solve the inverse problem. To improve the reconstruction quality, we consider the refraction effect of sound waves in the non-uniform temperature field and estimate the sound wave propagation path model in the reconstruction method. The shooting method with improved Powell algorithms is used to solve the propagation path model and obtain the relationship between the acoustic travel-time over the propagation path and temperature distribution. Simulations are implemented to evaluate the effectiveness of the proposed reconstruction method. The results indicate that compared with other methods, the new reconstruction method that considers the refraction effect can reconstruct temperature distribution with higher accuracy and better anti-noise ability. Experimental results also demonstrate that the temperature distribution can be reconstructed effectively by the proposed method.

关键词： Acoustic tomography Temperature distribution reconstruction radial basis function approximation Refraction effect of sound wave Reconstruction quality

来源：评论

学校读者我要写书评

暂无评论

Acoustic tomography system for online monitoring of temperature fields

引用

IET SCIENCE MEASUREMENT & TECHNOLOGY 2017年第5期11卷 623-630页

作者： Yan, Hua Ma, Zhao Zhou, Ying Gang Shenyang Univ Technol Sch Informat Sci & Engn Shenyang 110870 Liaoning Peoples R China

For online monitoring of complex temperature distributions, an acoustic tomography system based on sound travel-time measurement is developed. For coping with the reverberation phenomenon in actual measurement, an anti-reflection interference measurement method for sound travel-time is proposed based on cross-correlation and peak recognition. In view of the fact the pixel number provided by commonly used reconstruction algorithms, such as least-squares methods, is very limited, radial basis function approximation and regularisation technique are used, which leads to the pixel number of the reconstruction image increasing dramatically. Mixed programming with LabVIEW and MATLAB is used. Queue structure is adopted to make data acquiring program and data processing program parallel. Test results show that the system can run normally as designed. The measurement values of sound travel-time acquired by the proposed method are stable even in strong reflection interference. Test results show that the system can run normally as designed. The measurement values of sound travel-time acquired by the proposed method are stable even in strong reflection interference. The temperature fields reconstructed are coincided with actual fields, and correctly reflect the temperature changes in the measured area with the heater number, heater location and heating time.

关键词： temperature measurement acoustic tomography temperature distribution acoustic variables measurement time measurement reverberation acoustic wave interference acoustic correlation least squares approximations approximation theory image recognition image reconstruction virtual instrumentation mathematics computing data acquisition acoustic tomography system complex temperature distribution monitoring sound traveltime measurement reverberation phenomenon antireflection interference measurement method cross-correlation peak recognition image reconstruction algorithm least-square method radial basis function approximation regularisation technique LabVIEW programming data processing program data acquiring program queue structure MATLAB programming

来源：评论

学校读者我要写书评

暂无评论

Surface Reconstruction Based on Hierarchical Floating radial basis functions

引用

COMPUTER GRAPHICS FORUM 2010年第6期29卷 1854-1864页

作者： Suessmuth, J. Meyer, Q. Greiner, G. Univ Erlangen Nurnberg Comp Graph Grp D-8520 Erlangen Germany

In this paper we address the problem of optimal centre placement for scattered data approximation using radial basis functions (RBFs) by introducing the concept of floating centres. Given an initial least-squares solution, we optimize the positions and the weights of the RBF centres by minimizing a non-linear error function. By optimizing the centre positions, we obtain better approximations with a lower number of centres, which improves the numerical stability of the fitting procedure. We combine the non-linear RBF fitting with a hierarchical domain decomposition technique. This provides a powerful tool for surface reconstruction from oriented point samples. By directly incorporating point normal vectors into the optimization process, we avoid the use of off-surface points which results in less computational overhead and reduces undesired surface artefacts. We demonstrate that the proposed surface reconstruction technique is as robust as recent methods, which compute the indicator function of the solid described by the point samples. In contrast to indicator function based methods, our method computes a global distance field that can directly be used for shape registration.

关键词： surface reconstruction radial basis function approximation floating centres signed distance function

来源：评论

学校读者我要写书评

暂无评论

Surface interpolation with radial basis functions for medical imaging

引用

IEEE TRANSACTIONS ON MEDICAL IMAGING 1997年第1期16卷 96-107页

作者： Carr, JC Fright, WR Beatson, RK UNIV CANTERBURY DEPT ELECT & ELECT ENGN CHRISTCHURCH 1 NEW ZEALAND CHRISTCHURCH HOSP DEPT MED PHYS & BIOENGN CHRISTCHURCH NEW ZEALAND UNIV CANTERBURY DEPT MATH & STAT CHRISTCHURCH 1 NEW ZEALAND

radial basis functions are presented as a practical solution to the problem of interpolating incomplete surfaces derived from three-dimensional (3-D) medical graphics, The specific application considered is the design of cranial implants for the repair of defects, usually holes, in the skull, radial basis functions impose few restrictions on the geometry of the interpolation centers and are suited to problems where the interpolation centers do not form a regular grid. However, their high computational requirements have previously limited their use to problems where the number of interpolation centers is small (<300). Recently developed fast evaluation techniques have overcome these Limitations and made radial basis interpolation a practical approach for larger data sets, In this paper radial basis functions are fitted to depth-maps of the skull's surface, obtained from X-ray computed tomography (CT) data using ray-tracing techniques. They are used to smoothly interpolate the surface of the skull across defect regions, The resulting mathematical description of the skull's surface can be evaluated at any desired resolution to be rendered on a graphics workstation or to generate instructions for operating a computer numerically controlled (CNC) mill.

关键词： CT imaging medical graphics radial basis function approximation surface interpolation titanium cranioplasty

来源：评论

学校读者我要写书评

暂无评论

Adaptive nonlinear observer augmented by radial basis neural network for a nonlinear sensorless control of an induction machine

引用

INTERNATIONAL JOURNAL OF AUTOMATION AND CONTROL 2018年第1期12卷 27-43页

作者： Boufadene, Mourad Belkheiri, Mohammed Rabhi, Abdelhamid Univ Amar Telidji Laghouat Lab Telecommun Signals & Syst PB 37G Ghradaia Rd Laghouat 03000 Algeria Univ Picardie Jules Verne Lab Modeling Informat & Syst 33 Rue St Leu F-80039 Amiens 1 France

This paper presents adaptive neural network nonlinear observer associated with a sensor less nonlinear feedback linearisation controller for induction machine. The proposed observer is used to estimate the mechanical speed using the stator currents measurements and the supplied input voltages;whereas the load torque (unknown disturbance) is estimated using online radial basis neural network function approximation. The stability of the proposed controller-observer is achieved using Lyapunov function. Hence, simulation results have been performed under MATLAB/Simulink shows clearly the performance of the proposed algorithm.

关键词： sensorless control neural network observer adaptive observer load torque estimation induction machine feedback linearisation control mechanical speed estimation radial basis function approximation field oriented control FOC

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：