• 제목/요약/키워드: radial basis functions

검색결과 108건 처리시간 0.023초

보조벡터 머신을 이용한 시계열 예측에 관한 연구 (A study on the Time Series Prediction Using the Support Vector Machine)

  • 강환일;정요원;송영기
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.315-315
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    • 2000
  • In this paper, we perform the time series prediction using the SVM(Support Vector Machine). We make use of two different loss functions and two different kernel functions; i) Quadratic and $\varepsilon$-insensitive loss function are used; ii) GRBF(Gaussian Radial Basis Function) and ERBF(Exponential Radial Basis Function) are used. Mackey-Glass time series are used for prediction. For both cases, we compare the results by the SVM to those by ANN(Artificial Neural Network) and show the better performance by SVM than that by ANN.

SOLVING PARTIAL DIFFERENTIAL ALGEBRAIC EQUATIONS BY COLLOCATION AND RADIAL BASIS FUNCTIONS

  • Bao, Wendi;Song, Yongzhong
    • Journal of applied mathematics & informatics
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    • 제30권5_6호
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    • pp.951-969
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    • 2012
  • In this paper, we propose a class of meshless collocation approaches for the solution of time dependent partial differential algebraic equations (PDAEs) in terms of a radial basis function interpolation numerical scheme. Kansa's method and the Hermite collocation method (HCM) for PDAEs are given. A sensitivity analysis of the solutions from different shape parameter c is obtained by numerical experiments. With use of the random collocation points, we have obtain the more accurate solution by the methods than those by the finite difference method for the PDAEs with index-2, i.e, we avoid the influence from an index jump of PDAEs in some degree. Several numerical experiments show that the methods are efficient.

Meshless local Petrov-Galerkin method for rotating Rayleigh beam

  • Panchore, Vijay
    • Structural Engineering and Mechanics
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    • 제81권5호
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    • pp.607-616
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    • 2022
  • In this work, the free vibration problem of a rotating Rayleigh beam is solved using the meshless Petrov-Galerkin method which is a truly meshless method. The Rayleigh beam includes rotatory inertia in addition to Euler-Bernoulli beam theory. The radial basis functions, which satisfy the Kronecker delta property, are used for the interpolation. The essential boundary conditions can be easily applied with radial basis functions. The results are obtained using six nodes within a subdomain. The results accurately match with the published literature. Also, the results with Euler-Bernoulli are obtained to compare the change in higher natural frequencies with change in the slenderness ratio (${\sqrt{A_0R^2/I_0}}$). The mass and stiffness matrices are derived where we get two stiffness matrices for the node and boundary respectively. The non-dimensional form is discussed as well.

Identification of Plastic Wastes by Using Fuzzy Radial Basis Function Neural Networks Classifier with Conditional Fuzzy C-Means Clustering

  • Roh, Seok-Beom;Oh, Sung-Kwun
    • Journal of Electrical Engineering and Technology
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    • 제11권6호
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    • pp.1872-1879
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    • 2016
  • The techniques to recycle and reuse plastics attract public attention. These public attraction and needs result in improving the recycling technique. However, the identification technique for black plastic wastes still have big problem that the spectrum extracted from near infrared radiation spectroscopy is not clear and is contaminated by noise. To overcome this problem, we apply Raman spectroscopy to extract a clear spectrum of plastic material. In addition, to improve the classification ability of fuzzy Radial Basis Function Neural Networks, we apply supervised learning based clustering method instead of unsupervised clustering method. The conditional fuzzy C-Means clustering method, which is a kind of supervised learning based clustering algorithms, is used to determine the location of radial basis functions. The conditional fuzzy C-Means clustering analyzes the data distribution over input space under the supervision of auxiliary information. The auxiliary information is defined by using k Nearest Neighbor approach.

APPROXIMATION METHOD FOR SCATTERED DATA FROM SHIFTS OF A RADIAL BASIS FUNCTION

  • Yoon, Jung-Ho
    • Journal of applied mathematics & informatics
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    • 제27권5_6호
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    • pp.1087-1095
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    • 2009
  • In this paper, we study approximation method from scattered data to the derivatives of a function f by a radial basis function $\phi$. For a given function f, we define a nearly interpolating function and discuss its accuracy. In particular, we are interested in using smooth functions $\phi$ which are (conditionally) positive definite. We estimate accuracy of approximation for the Sobolev space while the classical radial basis function interpolation applies to the so-called native space. We observe that our approximant provides spectral convergence order, as the density of the given data is getting smaller.

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The smooth topology optimization for bi-dimensional functionally graded structures using level set-based radial basis functions

  • Wonsik Jung;Thanh T. Banh;Nam G. Luu;Dongkyu Lee
    • Steel and Composite Structures
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    • 제47권5호
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    • pp.569-585
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    • 2023
  • This paper proposes an efficient approach for the structural topology optimization of bi-directional functionally graded structures by incorporating popular radial basis functions (RBFs) into an implicit level set (ILS) method. Compared to traditional element density-based methods, a level set (LS) description of material boundaries produces a smoother boundary description of the design. The paper develops RBF implicit modeling with multiquadric (MQ) splines, thin-plate spline (TPS), exponential spline (ES), and Gaussians (GS) to define the ILS function with high accuracy and smoothness. The optimization problem is formulated by considering RBF-based nodal densities as design variables and minimizing the compliance objective function. A LS-RBF optimization method is proposed to transform a Hamilton-Jacobi partial differential equation (PDE) into a system of coupled non-linear ordinary differential equations (ODEs) over the entire design domain using a collocation formulation of the method of lines design variables. The paper presents detailed mathematical expressions for BiDFG beams topology optimization with two different material models: continuum functionally graded (CFG) and mechanical functionally graded (MFG). Several numerical examples are presented to verify the method's efficiency, reliability, and success in accuracy, convergence speed, and insensitivity to initial designs in the topology optimization of two-dimensional (2D) structures. Overall, the paper presents a novel and efficient approach to topology optimization that can handle bi-directional functionally graded structures with complex geometries.

Point interpolation method based on local residual formulation using radial basis functions

  • Liu, G.R.;Yan, L.;Wang, J.G.;Gu, Y.T.
    • Structural Engineering and Mechanics
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    • 제14권6호
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    • pp.713-732
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    • 2002
  • A local radial point interpolation method (LRPIM) based on local residual formulation is presented and applied to solid mechanics in this paper. In LRPIM, the trial function is constructed by the radial point interpolation method (PIM) and establishes discrete equations through a local residual formulation, which can be carried out nodes by nodes. Therefore, element connectivity for trial function and background mesh for integration is not necessary. Radial PIM is used for interpolation so that singularity in polynomial PIM may be avoided. Essential boundary conditions can be imposed by a straightforward and effective manner due to its Delta properties. Moreover, the approximation quality of the radial PIM is evaluated by the surface fitting of given functions. Numerical performance for this LRPIM method is further studied through several numerical examples of solid mechanics.

An Elliptical Basis Function Network for Classification of Remote-Sensing Images

  • Luo, Jian-Cheng;Chen, Qiu-Xiao;Zheng, Jiang;Leung, Yee;Ma, Jiang-Hong
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.1326-1328
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    • 2003
  • An elliptical basis function (EBF) network is proposed in this study for the classification of remotely sensed images. Though similar in structure, the EBF network differs from the well-known radial basis function (RBF) network by incorporating full covariance matrices and uses the expectation-maximization (EM) algorithm to estimate the basis functions. Since remotely sensed data often take on mixture -density distributions in the feature space, the proposed network not only possesses the advantage of the RBF mechanism but also utilizes the EM algorithm to compute the maximum likelihood estimates of the mean vectors and covariance matrices of a Gaussian mixture distribution in the training phase. Experimental results show that the EM-based EBF network is faster in training, more accurate, and simpler in structure.

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무요소법(RPIM)을 이용한 구조 요소의 응력해석 (The Stress Analysis of Structural Element Using Meshfree Method(RPIM))

  • 한상을;양재근;주정식
    • 한국전산구조공학회논문집
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    • 제20권3호
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    • pp.311-319
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    • 2007
  • 본 연구에서는 구조 요소의 응력해석을 위한 무요소 RPIM(Meshfree Radial Point Interpolation Methods)법을 제시한다. 이를 위하여 먼저 무요소법의 형상함수와 무요소 RPIM법의 정식화 과정 및 프로그래밍을 간략히 한다. 절점보간법은 방사기저함수와 다항기저함수를 포함하고 있고 이 중 다항기저함수는 특이성문제를 극복할 수 있다. 게다가 무요소 RPIM법의 보간함수는 영향영역의 절점을 통과하고 형상함수는 크로네커 델타 성질을 갖고 있으므로 최소자승법에 기반을 둔 무요소법보다 쉽게 필수경계조건을 만족시킨다. 본 연구의 정확성을 확인하기 위하여, 캔틸레버형 평판, 유공평판, 속이 빈 원통 문제의 수치예제를 수행하고 이론 해와 유한요소법 결과를 비교, 분석한다.

A radial point interpolation method for 1D contaminant transport modelling through landfill liners

  • Praveen Kumar, R.;Dodagoudar, G.R.
    • Geomechanics and Engineering
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    • 제2권2호
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    • pp.141-156
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    • 2010
  • In the framework of meshfree methods, a new methodology is developed based on radial point interpolation method (RPIM). This methodology is applied to a one-dimensional contaminant transport modelling in the saturated porous media. The one-dimensional form of advection-dispersion equation involving reactive contaminant is considered in the analysis. The Galerkin weak form of the governing equation is formulated using 1D meshfree shape functions constructed using thin plate spline radial basis functions. MATLAB code is developed to obtain the numerical solution. Numerical examples representing various phenomena, which occur during migration of contaminants, are presented to illustrate the applicability of the proposed method and the results are compared with those obtained from the analytical and finite element solutions. The proposed RPIM has generated results with no oscillations and they are insensitive to Peclet constraints. In order to test the practical applicability and performance of the RPIM, three case studies of contaminant transport through the landfill liners are presented. A good agreement is obtained between the results of the RPIM and the field investigation data.