75 research outputs found

    Homotopy analysis method for solving multi-term linear and nonlinear diffusion–wave equations of fractional order

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    AbstractIn this paper we have used the homotopy analysis method (HAM) to obtain solutions of multi-term linear and nonlinear diffusion–wave equations of fractional order. The fractional derivative is described in the Caputo sense. Some illustrative examples have been presented

    Non-parallel plane Rayleigh Benard convection in cylindrical geometry

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    This paper considers the effect of a perturbed wall in regard to the classical Benard convection problem in which the lower rigid surface is of the form z=ε2g(s)z=ε^2 g(s), s=ε r, in axisymmetric cylindrical polar coordinates (r,ϕ,z). The boundary conditions at s=0 for the linear amplitude equation are found and it is shown that these conditions are different from those which apply to the nonlinear problem investigated by Brown and Stewartson [1], representing the distribution of convection cells near the center

    Generalizing Homotopy Analysis Method to Solve System of Integral Equations

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    This paper presents the application of the Homotopy Analysis Method (HAM) and Homotopy Perturbation Method (HPM) for solving systems of integral equations. HAM and HPM are two analytical methods to solve linear and nonlinear equations which can be used to obtain the numerical solution. The HAM contains the auxiliary parameter h, provide us with a simple way to adjust and control the convergence region of solution series. The results show that HAM is a very efficient method and that HPM is a special case of HAM

    Adomian Decomposition Method for Approximating the Solution of the Parabolic Equations

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    Abstract In this paper, the Adomian decomposition method for solving the linear and nonlinear parabolic equations is implemented with appropriate initial conditions. In comparison with existing techniques, the decomposition method is highly effective in terms of accuracy and rapid convergence. The numerical results obtained by this way have been compared with the exact solution to show the efficiency of the method. Mathematics Subject Classification: 35K9

    Solving a system of nonlinear integral equations by an RBF network

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    AbstractIn this paper, a novel learning strategy for radial basis function networks (RBFN) is proposed. By adjusting the parameters of the hidden layer, including the RBF centers and widths, the weights of the output layer are adapted by local optimization methods. A new local optimization algorithm based on a combination of the gradient and Newton methods is introduced. The efficiency of some local optimization methods to update the weights of RBFN is studied in solving systems of nonlinear integral equations
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