Haiyan Tian¹, Sergiy Reustkiy², C.S. Chen¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.3, No.4, pp. 169-176, 2007, DOI:10.3970/icces.2007.003.169

Abstract We introduce a new type of basis functions in this paper to approximate a scattered data set. We test our basis functions on recovering the well-known Franke's function given by scattered data. We then use these basis functions in Kansa's method for solving Helmholtz equations. To demonstrate our proposed approach, we compare the numerical solutions with analytic solutions. The numerical results show that our approach is accurate and efficient. More >

L. Mai-Cao¹, T. Tran-Cong²

CMES-Computer Modeling in Engineering & Sciences, Vol.7, No.2, pp. 149-172, 2005, DOI:10.3970/cmes.2005.007.149

Abstract The Indirect Radial Basis Function Network (IRBFN) method has been reported to be a highly accurate tool for approximating multivariate functions and solving elliptic partial differential equations (PDEs). The present method is a truly meshless method as defined in [\citet *{Atluri_Shen_02a}]. A recent development of the method for solving transient problems is presented in this paper. Two numerical schemes combining the IRBFN method with different time integration techniques based on either fully or semi-discrete framework are proposed. The two schemes are implemented making use of Hardy's multiquadrics (MQ) and Duchon's thin plate splines (TPS). Some example problems are solved by… More >

Nam Mai-Duy¹

CMES-Computer Modeling in Engineering & Sciences, Vol.6, No.2, pp. 209-226, 2004, DOI:10.3970/cmes.2004.006.209

Abstract This paper is concerned with the use of the indirect radial basis function network (RBFN) method in solving partial differential equations (PDEs) with scattered points. Indirect RBFNs (Mai-Duy and Tran-Cong, 2001a), which are based on an integration process, are employed to approximate the solution of PDEs via point collocation mechanism in the set of randomly distributed points. The method is tested with the solution of Poisson's equations and the Navier-Stokes equations (Boussinesq material). Good results are obtained using relatively low numbers of data points. For example, the natural convection flow in a square cavity at Rayleigh number of 1.e6 is… More >

Wei Chen^{1, 2}, Tingzhu Sun^{1, 2}, Fangming Bi^{1, 2, *}, Tongfeng Sun^{1, 2}, Chaogang Tang^{1, 2}, Biruk Assefa^{1, 3}

Journal of New Media, Vol.1, No.1, pp. 35-44, 2019, DOI:10.32604/jnm.2019.05803

Abstract Image restoration is an image processing technology with great practical value in the field of computer vision. It is a computer technology that estimates the image information of the damaged area according to the residual image information of the damaged image and carries out automatic repair. This article firstly classify and summarize image restoration algorithms, and describe recent advances in the research respectively from three aspects including image restoration based on partial differential equation, based on the texture of image restoration and based on deep learning, then make the brief analysis of digital image restoration of subjective and objective evaluation… More >

Hongwei Guo³, Xiaoying Zhuang^3,4,5, Timon Rabczuk^1,2,*

CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 433-456, 2019, DOI:10.32604/cmc.2019.06660

Abstract In this paper, a deep collocation method (DCM) for thin plate bending problems is proposed. This method takes advantage of computational graphs and backpropagation algorithms involved in deep learning. Besides, the proposed DCM is based on a feedforward deep neural network (DNN) and differs from most previous applications of deep learning for mechanical problems. First, batches of randomly distributed collocation points are initially generated inside the domain and along the boundaries. A loss function is built with the aim that the governing partial differential equations (PDEs) of Kirchhoff plate bending problems, and the boundary/initial conditions are minimised at those collocation… More >

Jiaquan Xie^1,3,*, Fuqiang Zhao^1,3, Zhibin Yao^1,3, Jun Zhang^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.115, No.1, pp. 67-84, 2018, DOI:10.3970/cmes.2018.115.067

Abstract In this paper, the three-variable shifted Jacobi operational matrix of fractional derivatives is used together with the collocation method for numerical solution of three-dimensional multi-term fractional-order PDEs with variable coefficients. The main characteristic behind this approach is that it reduces such problems to those of solving a system of algebraic equations which greatly simplifying the problem. The approximate solutions of nonlinear fractional PDEs with variable coefficients thus obtained by three-variable shifted Jacobi polynomials are compared with the exact solutions. Furthermore some theorems and lemmas are introduced to verify the convergence results of our algorithm. Lastly, several numerical examples are presented… More >

S. Vahdati¹, D. Mirzaei²

CMES-Computer Modeling in Engineering & Sciences, Vol.109-110, No.3, pp. 247-262, 2015, DOI:10.3970/cmes.2015.109.247

Abstract In this paper we present a meshless collocation method based on the moving least squares (MLS) approximation for numerical solution of the multiasset (d-dimensional) American option in financial mathematics. This problem is modeled by the Black-Scholes equation with moving boundary conditions. A penalty approach is applied to convert the original problem to one in a fixed domain. In finite parts, boundary conditions satisfy in associated (d-1)-dimensional Black-Scholes equations while in infinity they approach to zero. All equations are treated by the proposed meshless approximation method where the method of lines is employed for handling the time variable. Numerical examples for… More >

H. Rafieayan Zadeh¹, M. Mohammadi^1,2, E. Babolian¹

CMES-Computer Modeling in Engineering & Sciences, Vol.108, No.6, pp. 375-396, 2015, DOI:10.3970/cmes.2015.108.375

Abstract A local reproducing kernel method based on spatial trial space spanned by the Newton basis functions in the native Hilbert space of the reproducing kernel is proposed. It is a truly meshless approach which uses the local sub clusters of domain nodes for approximation of the arbitrary field. It leads to a system of ordinary differential equations (ODEs) for the time-dependent partial differential equations (PDEs). An adaptive algorithm, so-called adaptive residual subsampling, is used to adjust nodes in order to remove oscillations which are caused by a sharp gradient. The method is applied for solving the Allen-Cahn and Burgers’ equations.… More >

S.Yu. Reutskiy¹

CMES-Computer Modeling in Engineering & Sciences, Vol.99, No.4, pp. 327-349, 2014, DOI:10.3970/cmes.2014.099.327

Abstract The paper presents a new meshless numerical method for solving 2D and 3D boundary value problems (BVPs) with elliptic PDEs of general form. The coefficients of the PDEs including the main operator part are spatially dependent functions. The key idea of the method is the use of the basis functions which satisfy the homogeneous boundary conditions of the problem. This allows us to seek an approximate solution in the form which satisfies the boundary conditions of the initial problem with any choice of the free parameters. As a result we separate approximation of the boundary conditions and approximation of the… More >

N. Pham-Sy¹, C.-D. Tran¹, T.-T. Hoang-Trieu¹, N. Mai-Duy¹, T. Tran-Cong¹

CMES-Computer Modeling in Engineering & Sciences, Vol.92, No.1, pp. 1-31, 2013, DOI:10.3970/cmes.2013.092.001

Abstract Compact Local Integrated Radial Basis Function (CLIRBF) methods based on Cartesian grids can be effective numerical methods for solving partial differential equations (PDEs) for fluid flow problems. The combination of the domain decomposition method and function approximation using CLIRBF methods yields an effective coarse-grained parallel processing approach. This approach has enabled not only each sub-domain in the original analysis domain to be discretised by a separate CLIRBF network but also compact local stencils to be independently treated. The present algorithm, namely parallel CLIRBF, achieves higher throughput in solving large scale problems by, firstly, parallel processing of sub-regions which constitute the… More >