Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
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Article Citation - WoS: 76Citation - Scopus: 82On Shifted Jacobi Spectral Approximations for Solving Fractional Differential Equations(Elsevier Science inc, 2013) Bhrawy, A. H.; Baleanu, D.; Ezz-Eldien, S. S.; Doha, E. H.In this paper, a new formula of Caputo fractional-order derivatives of shifted Jacobi polynomials of any degree in terms of shifted Jacobi polynomials themselves is proved. We discuss a direct solution technique for linear multi-order fractional differential equations (FDEs) subject to nonhomogeneous initial conditions using a shifted Jacobi tau approximation. A quadrature shifted Jacobi tau (Q-SJT) approximation is introduced for the solution of linear multi-order FDEs with variable coefficients. We also propose a shifted Jacobi collocation technique for solving nonlinear multi-order fractional initial value. problems. The advantages of using the proposed techniques are discussed and we compare them with other existing methods. We investigate some illustrative examples of FDEs including linear and nonlinear terms. We demonstrate the high accuracy and the efficiency of the proposed techniques. (C) 2013 Elsevier Inc. All rights reserved.Article Citation - WoS: 137Citation - Scopus: 151Variational Iteration Method for the Burgers' Flow With Fractional Derivatives-New Lagrange Multipliers(Elsevier Science inc, 2013) Baleanu, Dumitru; Wu, Guo-ChengThe flow through porous media can be better described by fractional models than the classical ones since they include inherently memory effects caused by obstacles in the structures. The variational iteration method was extended to find approximate solutions of fractional differential equations with the Caputo derivatives, but the Lagrange multipliers of the method were not identified explicitly. In this paper, the Lagrange multiplier is determined in a more accurate way and some new variational iteration formulae are presented. (C) 2013 Elsevier Inc. All rights reserved.Article Citation - WoS: 82Citation - Scopus: 85Fractional Differential Equations of Caputo-Katugampola Type and Numerical Solutions(Elsevier Science inc, 2017) Baleanu, Dumitru; Bai, Yunru; Wu, Guocheng; Zeng, ShengdaThis paper is concerned with a numerical method for solving generalized fractional differential equation of Caputo-Katugampola derivative. A corresponding discretization technique is proposed. Numerical solutions are obtained and convergence of numerical formulae is discussed. The convergence speed arrives at O(Delta T1-alpha). Numerical examples are given to test the accuracy. (C) 2017 Elsevier Inc. All rights reserved.Article Citation - WoS: 139Citation - Scopus: 156Solving Differential Equations of Fractional Order Using an Optimization Technique Based on Training Artificial Neural Network(Elsevier Science inc, 2017) Ahmadian, A.; Effati, S.; Salahshour, S.; Baleanu, D.; Pakdaman, M.The current study aims to approximate the solution of fractional differential equations (FDEs) by using the fundamental properties of artificial neural networks (ANNs) for function approximation. In the first step, we derive an approximate solution of fractional differential equation (FDE) by using ANNs. In the second step, an optimization approach is exploited to adjust the weights of ANNs such that the approximated solution satisfies the FDE. Different types of FDEs including linear and nonlinear terms are solved to illustrate the ability of the method. In addition, the present scheme is compared with the analytical solution and a number of existing numerical techniques to show the efficiency of ANNs with high accuracy, fast convergence and low use of memory for solving the FDEs. (C) 2016 Elsevier Inc. All rights reserved.