Stochastic Processes and their Applications, ISSN 0304-4149, 05/2020, Volume 130, Issue 5, pp. 2675 - 2692

In this paper, we investigate the optimal strong convergence rate of numerical approximations for the Cox–Ingersoll–Ross model driven by fractional Brownian...

Cox–Ingersoll–Ross model | Optimal strong convergence rate | Malliavin calculus | Fractional Brownian motion | Backward Euler scheme | DISCRETIZATION | APPROXIMATION | Cox-Ingersoll-Ross model | SDES | STATISTICS & PROBABILITY | CIR

Cox–Ingersoll–Ross model | Optimal strong convergence rate | Malliavin calculus | Fractional Brownian motion | Backward Euler scheme | DISCRETIZATION | APPROXIMATION | Cox-Ingersoll-Ross model | SDES | STATISTICS & PROBABILITY | CIR

Journal Article

Journal of Computational and Applied Mathematics, ISSN 0377-0427, 07/2015, Volume 282, pp. 44 - 53

This paper is a continuation of our previous paper, in which, the second author, with Mao and Szpruch examined the almost sure stability of the Euler–Maruyama...

Monotone-type condition | Stochastic delay differential equations | Exponential stability | Backward Euler–Maruyama method | Almost sure stability | Backward Euler-Maruyama method | MATHEMATICS, APPLIED | NUMERICAL-SOLUTIONS | Backward Euler Maruyama method | ASYMPTOTIC STABILITY | DISCRETIZATIONS | Differential equations

Monotone-type condition | Stochastic delay differential equations | Exponential stability | Backward Euler–Maruyama method | Almost sure stability | Backward Euler-Maruyama method | MATHEMATICS, APPLIED | NUMERICAL-SOLUTIONS | Backward Euler Maruyama method | ASYMPTOTIC STABILITY | DISCRETIZATIONS | Differential equations

Journal Article

3.
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Implicit Euler numerical scheme and chattering-free implementation of sliding mode systems

Systems & Control Letters, ISSN 0167-6911, 2010, Volume 59, Issue 5, pp. 284 - 293

In this paper it is shown that the implicit Euler time-discretization of some classes of switching systems with sliding modes, yields a very good stabilization...

Sliding modes | Switching systems | Mixed linear complementarity problem | Maximal monotone mappings | Backward Euler algorithm | ZOH discretization | Complementarity problems | Filippov’s differential inclusions | Filippov's differential inclusions | FRICTION | INTERSECTING SWITCHING SURFACES | DRIVES | DISCRETIZATION BEHAVIORS | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | AUTOMATION & CONTROL SYSTEMS | Algorithms | Modeling and Simulation | Mathematics | Optimization and Control | Computer Science

Sliding modes | Switching systems | Mixed linear complementarity problem | Maximal monotone mappings | Backward Euler algorithm | ZOH discretization | Complementarity problems | Filippov’s differential inclusions | Filippov's differential inclusions | FRICTION | INTERSECTING SWITCHING SURFACES | DRIVES | DISCRETIZATION BEHAVIORS | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | AUTOMATION & CONTROL SYSTEMS | Algorithms | Modeling and Simulation | Mathematics | Optimization and Control | Computer Science

Journal Article

The Annals of Applied Probability, ISSN 1050-5164, 8/2012, Volume 22, Issue 4, pp. 1611 - 1641

On the one hand, the explicit Euler scheme fails to converge strongly to the exact solution of a stochastic differential equation (SDE) with a superlinearly...

Platens | Error rates | Approximation | Eulers method | Roots of functions | Numerical methods | Stochastic processes | Differential equations | Coefficients | Perceptron convergence procedure | Strong approximation | Nonglobally Lipschitz | Tamed Euler scheme | Implicit Euler scheme | Superlinearly growing coefficient | Backward Euler scheme | Euler scheme | Euler-Maruyama | Stochastic differential equation | nonglobally Lipschitz | STOCHASTIC DIFFERENTIAL-EQUATIONS | tamed Euler scheme | BEHAVIOR | strong approximation | UNIFORM APPROXIMATION | STATISTICS & PROBABILITY | IMPLICIT METHODS | superlinearly growing coefficient | SCHEME | stochastic differential equation | implicit Euler scheme | SYSTEMS | 65C30 | Euler–Maruyama

Platens | Error rates | Approximation | Eulers method | Roots of functions | Numerical methods | Stochastic processes | Differential equations | Coefficients | Perceptron convergence procedure | Strong approximation | Nonglobally Lipschitz | Tamed Euler scheme | Implicit Euler scheme | Superlinearly growing coefficient | Backward Euler scheme | Euler scheme | Euler-Maruyama | Stochastic differential equation | nonglobally Lipschitz | STOCHASTIC DIFFERENTIAL-EQUATIONS | tamed Euler scheme | BEHAVIOR | strong approximation | UNIFORM APPROXIMATION | STATISTICS & PROBABILITY | IMPLICIT METHODS | superlinearly growing coefficient | SCHEME | stochastic differential equation | implicit Euler scheme | SYSTEMS | 65C30 | Euler–Maruyama

Journal Article

Numerical Methods for Partial Differential Equations, ISSN 0749-159X, 05/2019, Volume 35, Issue 3, pp. 1113 - 1133

In the present article we study the numerics of the viscous Cahn–Hilliard–Navier–Stokes model, endowed with dynamic boundary conditions which allow us to take...

Navier–Stokes equations | viscous Cahn–Hilliard equations | finite element method | dynamic boundary conditions | moving contact line | well‐posedness | backward Euler scheme | well-posedness | SYSTEM | MATHEMATICS, APPLIED | INCOMPRESSIBLE FLUIDS | APPROXIMATION | viscous Cahn-Hilliard equations | TIME | 2-PHASE FLUID | DYNAMICS | FLOWS | EFFICIENT | DIFFUSE INTERFACE MODEL | PHASE-FIELD MODEL | Navier-Stokes equations | Numerical analysis | Stability | Computational fluid dynamics | Computer simulation | Fluid flow | Boundary conditions | Mathematical models | Moving walls | Analysis of PDEs | Mathematics

Navier–Stokes equations | viscous Cahn–Hilliard equations | finite element method | dynamic boundary conditions | moving contact line | well‐posedness | backward Euler scheme | well-posedness | SYSTEM | MATHEMATICS, APPLIED | INCOMPRESSIBLE FLUIDS | APPROXIMATION | viscous Cahn-Hilliard equations | TIME | 2-PHASE FLUID | DYNAMICS | FLOWS | EFFICIENT | DIFFUSE INTERFACE MODEL | PHASE-FIELD MODEL | Navier-Stokes equations | Numerical analysis | Stability | Computational fluid dynamics | Computer simulation | Fluid flow | Boundary conditions | Mathematical models | Moving walls | Analysis of PDEs | Mathematics

Journal Article

Numerical Methods for Partial Differential Equations, ISSN 0749-159X, 05/2018, Volume 34, Issue 3, pp. 938 - 958

A backward Euler alternating direction implicit (ADI) difference scheme is formulated and analyzed for the three‐dimensional fractional evolution equation. In...

convolution quadrature | difference scheme | numerical experiments | unconditional stability and convergence | three‐dimensional fractional evolution equation | backward Euler ADI | three-dimensional fractional evolution equation | MATHEMATICS, APPLIED | MEMORY TERM | WEAKLY SINGULAR KERNEL | ADI | SUB-DIFFUSION EQUATION | HEAT-EQUATION | PARTIAL INTEGRODIFFERENTIAL EQUATIONS | WAVE-EQUATION | SPLINE COLLOCATION METHODS | NUMERICAL-SIMULATION | Alternating direction implicit methods | Convolution | Quadratic forms | Norms | Evolution | Stability analysis | Finite difference method

convolution quadrature | difference scheme | numerical experiments | unconditional stability and convergence | three‐dimensional fractional evolution equation | backward Euler ADI | three-dimensional fractional evolution equation | MATHEMATICS, APPLIED | MEMORY TERM | WEAKLY SINGULAR KERNEL | ADI | SUB-DIFFUSION EQUATION | HEAT-EQUATION | PARTIAL INTEGRODIFFERENTIAL EQUATIONS | WAVE-EQUATION | SPLINE COLLOCATION METHODS | NUMERICAL-SIMULATION | Alternating direction implicit methods | Convolution | Quadratic forms | Norms | Evolution | Stability analysis | Finite difference method

Journal Article

Calcolo, ISSN 0008-0624, 12/2015, Volume 52, Issue 4, pp. 445 - 473

In the paper, our main aim is to investigate the strong convergence and almost surely exponential stability of an implicit numerical approximation under...

65C20 | Strong convergence | Backward Euler–Maruyama method | Numerical Analysis | Stochastic differential delay equation | Polynomial growth condition | Mathematics | Theory of Computation | Discrete semi-martingale convergence theorem | Almost surely exponential stability | MOMENT EXPONENTIAL STABILITY | STABILIZATION | Backward Euler-Maruyama method | TIME | MEAN-SQUARE | DISCRETIZATIONS | MATHEMATICS | SURE | NUMERICAL-SOLUTIONS | COEFFICIENTS | SYSTEMS | ASYMPTOTIC STABILITY

65C20 | Strong convergence | Backward Euler–Maruyama method | Numerical Analysis | Stochastic differential delay equation | Polynomial growth condition | Mathematics | Theory of Computation | Discrete semi-martingale convergence theorem | Almost surely exponential stability | MOMENT EXPONENTIAL STABILITY | STABILIZATION | Backward Euler-Maruyama method | TIME | MEAN-SQUARE | DISCRETIZATIONS | MATHEMATICS | SURE | NUMERICAL-SOLUTIONS | COEFFICIENTS | SYSTEMS | ASYMPTOTIC STABILITY

Journal Article

Journal of Computational and Applied Mathematics, ISSN 0377-0427, 04/2015, Volume 278, pp. 258 - 277

This paper establishes the boundedness, convergence and stability of the two classes of theta schemes, namely split-step theta (SST) scheme and stochastic...

Stochastic linear theta scheme | Exponential mean square stability | Stochastic differential delay equation (SDDE) | Strong convergence rate | Split-step theta scheme | SYSTEM | MILSTEIN SCHEME | MATHEMATICS, APPLIED | STOCHASTIC DIFFERENTIAL-EQUATIONS | MARUYAMA METHOD | APPROXIMATIONS | STABILITY | STRONG-CONVERGENCE RATES | NUMERICAL-SOLUTIONS | BACKWARD EULER METHOD | DELAY EQUATIONS

Stochastic linear theta scheme | Exponential mean square stability | Stochastic differential delay equation (SDDE) | Strong convergence rate | Split-step theta scheme | SYSTEM | MILSTEIN SCHEME | MATHEMATICS, APPLIED | STOCHASTIC DIFFERENTIAL-EQUATIONS | MARUYAMA METHOD | APPROXIMATIONS | STABILITY | STRONG-CONVERGENCE RATES | NUMERICAL-SOLUTIONS | BACKWARD EULER METHOD | DELAY EQUATIONS

Journal Article

Advances in Computational Mathematics, ISSN 1019-7168, 12/2016, Volume 42, Issue 6, pp. 1311 - 1330

In this paper, we focus on a linearized backward Euler scheme with a Galerkin finite element approximation for the time-dependent nonlinear Schrödinger...

Visualization | Computational Mathematics and Numerical Analysis | Mathematical and Computational Biology | Unconditional convergence | Optimal error estimate | Mathematics | Time-dependent Schrödinger equation | Mathematical Modeling and Industrial Mathematics | Computational Science and Engineering | Galerkin finite element method | Backward Euler method | 65N30 | MATHEMATICS, APPLIED | NAVIER-STOKES EQUATIONS | PARABOLIC EQUATIONS | GINZBURG-LANDAU EQUATIONS | GALERKIN METHODS | IMPLICIT/EXPLICIT SCHEME | Time-dependent Schrodinger equation | FINITE-ELEMENT-METHOD | Analysis | Approximation theory | Schrodinger equation

Visualization | Computational Mathematics and Numerical Analysis | Mathematical and Computational Biology | Unconditional convergence | Optimal error estimate | Mathematics | Time-dependent Schrödinger equation | Mathematical Modeling and Industrial Mathematics | Computational Science and Engineering | Galerkin finite element method | Backward Euler method | 65N30 | MATHEMATICS, APPLIED | NAVIER-STOKES EQUATIONS | PARABOLIC EQUATIONS | GINZBURG-LANDAU EQUATIONS | GALERKIN METHODS | IMPLICIT/EXPLICIT SCHEME | Time-dependent Schrodinger equation | FINITE-ELEMENT-METHOD | Analysis | Approximation theory | Schrodinger equation

Journal Article

Journal of Computational and Applied Mathematics, ISSN 0377-0427, 07/2018, Volume 336, pp. 8 - 29

This paper examines convergence and stability of the two classes of theta-Milstein schemes for stochastic differential equations (SDEs) with non-global...

Exponential mean-square stability | SDEs | Split-step theta-Milstein scheme | Stochastic theta-Milstein scheme | Strong convergence rate | MATHEMATICS, APPLIED | APPROXIMATIONS | TIME | RATES | BACKWARD EULER | MEAN-SQUARE STABILITY | SYSTEMS | DIFFUSION | LIPSCHITZ CONTINUOUS COEFFICIENTS | Differential equations

Exponential mean-square stability | SDEs | Split-step theta-Milstein scheme | Stochastic theta-Milstein scheme | Strong convergence rate | MATHEMATICS, APPLIED | APPROXIMATIONS | TIME | RATES | BACKWARD EULER | MEAN-SQUARE STABILITY | SYSTEMS | DIFFUSION | LIPSCHITZ CONTINUOUS COEFFICIENTS | Differential equations

Journal Article

Computational Methods in Applied Mathematics, ISSN 1609-4840, 04/2017, Volume 17, Issue 2, pp. 237 - 252

We introduce and analyze a discontinuous Petrov–Galerkin method with optimal test functions for the heat equation. The scheme is based on the backward Euler...

Backward Euler Scheme | Rothe’s Method | 65M15 | DPG Method with Optimal Test Functions | Least Squares Method | Ultra-Weak Formulation | 65M60 | Parabolic Problem | 65M12 | Heat Equation | Rothe's Method | MATHEMATICS, APPLIED | Rothe ' s Method | DOMINATED DIFFUSION-PROBLEMS | PROBLEMS II | SQUARES GALERKIN METHODS | PARABOLIC PROBLEMS | Test procedures | Galerkin method

Backward Euler Scheme | Rothe’s Method | 65M15 | DPG Method with Optimal Test Functions | Least Squares Method | Ultra-Weak Formulation | 65M60 | Parabolic Problem | 65M12 | Heat Equation | Rothe's Method | MATHEMATICS, APPLIED | Rothe ' s Method | DOMINATED DIFFUSION-PROBLEMS | PROBLEMS II | SQUARES GALERKIN METHODS | PARABOLIC PROBLEMS | Test procedures | Galerkin method

Journal Article

Applied Mathematics and Computation, ISSN 0096-3003, 10/2014, Volume 244, pp. 361 - 374

In this article we present robust, efficient and accurate fully implicit time-stepping schemes and nonlinear solvers for systems of reaction–diffusion...

Reaction–diffusion systems | Fractional-step [formula omitted] scheme | Backward Euler method | Newton method | Fully implicit time-stepping schemes | Crank–Nicolson method | Fractional-step θ scheme | Reaction-diffusion systems | Crank-Nicolson method | MATHEMATICS, APPLIED | FINITE-ELEMENTS | EXPLICIT METHODS | MODEL | PATTERN-FORMATION | Fractional-step theta scheme | TURING PATTERNS | DOMAINS | Mathematics - Numerical Analysis

Reaction–diffusion systems | Fractional-step [formula omitted] scheme | Backward Euler method | Newton method | Fully implicit time-stepping schemes | Crank–Nicolson method | Fractional-step θ scheme | Reaction-diffusion systems | Crank-Nicolson method | MATHEMATICS, APPLIED | FINITE-ELEMENTS | EXPLICIT METHODS | MODEL | PATTERN-FORMATION | Fractional-step theta scheme | TURING PATTERNS | DOMAINS | Mathematics - Numerical Analysis

Journal Article

STOCHASTIC PROCESSES AND THEIR APPLICATIONS, ISSN 0304-4149, 05/2013, Volume 123, Issue 5, pp. 1563 - 1587

In this paper, L-P convergence and almost sure convergence of the Milstein approximation of a partial differential equation of advection-diffusion type driven...

Advection-diffusion equation | EVOLUTION EQUATIONS | Almost sure convergence | APPROXIMATION | INEQUALITY | FINITE-ELEMENT METHODS | CONVOLUTIONS | STATISTICS & PROBABILITY | Stochastic partial differential equation | DRIVEN | Milstein scheme | ADDITIVE NOISE | Galerkin method | L-P convergence | Finite Element method | Backward Euler scheme | Differential equations

Advection-diffusion equation | EVOLUTION EQUATIONS | Almost sure convergence | APPROXIMATION | INEQUALITY | FINITE-ELEMENT METHODS | CONVOLUTIONS | STATISTICS & PROBABILITY | Stochastic partial differential equation | DRIVEN | Milstein scheme | ADDITIVE NOISE | Galerkin method | L-P convergence | Finite Element method | Backward Euler scheme | Differential equations

Journal Article

SIAM Journal on Numerical Analysis, ISSN 0036-1429, 2016, Volume 54, Issue 4, pp. 2323 - 2358

A posteriori error estimates for time discretization of the incompressible Stokes equations by pressure-correction methods are presented. We rigorously prove...

Reconstruction | BDF2 | Navier-stokes equations | Projection methods | A posteriori error analysis | Backward Euler | Fractional step methods | MATHEMATICS, APPLIED | projection methods | APPROXIMATIONS | ELLIPTIC RECONSTRUCTION | PARABOLIC PROBLEMS | fractional step methods | DISCRETIZATION | backward Euler | HEAT-EQUATION | reconstruction | CONVERGENCE | a posteriori error analysis | Navier-Stokes equations

Reconstruction | BDF2 | Navier-stokes equations | Projection methods | A posteriori error analysis | Backward Euler | Fractional step methods | MATHEMATICS, APPLIED | projection methods | APPROXIMATIONS | ELLIPTIC RECONSTRUCTION | PARABOLIC PROBLEMS | fractional step methods | DISCRETIZATION | backward Euler | HEAT-EQUATION | reconstruction | CONVERGENCE | a posteriori error analysis | Navier-Stokes equations

Journal Article

Journal of Scientific Computing, ISSN 0885-7474, 6/2016, Volume 67, Issue 3, pp. 955 - 987

This paper is concerned with the numerical approximation of stochastic ordinary differential equations, which satisfy a global monotonicity condition. This...

Computational Mathematics and Numerical Analysis | Stochastic differential equations | C-stability | Theoretical, Mathematical and Computational Physics | Mathematics | Projected Euler–Maruyama | Split-step backward Euler | Algorithms | 65C30 | Appl.Mathematics/Computational Methods of Engineering | Strong convergence rates | Global monotonicity condition | 65L20 | B-consistency | Analysis | Numerical analysis | Differential equations | Theorems | Mathematical analysis | Mathematical models | Drift | Stochasticity | Convergence

Computational Mathematics and Numerical Analysis | Stochastic differential equations | C-stability | Theoretical, Mathematical and Computational Physics | Mathematics | Projected Euler–Maruyama | Split-step backward Euler | Algorithms | 65C30 | Appl.Mathematics/Computational Methods of Engineering | Strong convergence rates | Global monotonicity condition | 65L20 | B-consistency | Analysis | Numerical analysis | Differential equations | Theorems | Mathematical analysis | Mathematical models | Drift | Stochasticity | Convergence

Journal Article

Journal of Applied Mathematics and Computing, ISSN 1598-5865, 2/2017, Volume 53, Issue 1, pp. 413 - 443

In this article we present a finite element scheme for solving a nonlocal parabolic problem involving the Dirichlet energy. For time discretization, we use...

65N15 | Computational Mathematics and Numerical Analysis | Kirchhoff equation | 65N12 | Mathematics | Theory of Computation | 35N30 | Newton iteration method | Nonlocal | Mathematics of Computing | Appl.Mathematics/Computational Methods of Engineering | Backward Euler method | 65N22 | MATHEMATICS | Newton teration method | MATHEMATICS, APPLIED | PARTIAL-DIFFERENTIAL-EQUATIONS | APPROXIMATIONS | Studies | Eulers equations | Dirichlet problem | Finite element analysis | Finite element method | Jacobian matrix | Applications of mathematics | Discretization | Mathematical analysis | Newton methods | Estimates

65N15 | Computational Mathematics and Numerical Analysis | Kirchhoff equation | 65N12 | Mathematics | Theory of Computation | 35N30 | Newton iteration method | Nonlocal | Mathematics of Computing | Appl.Mathematics/Computational Methods of Engineering | Backward Euler method | 65N22 | MATHEMATICS | Newton teration method | MATHEMATICS, APPLIED | PARTIAL-DIFFERENTIAL-EQUATIONS | APPROXIMATIONS | Studies | Eulers equations | Dirichlet problem | Finite element analysis | Finite element method | Jacobian matrix | Applications of mathematics | Discretization | Mathematical analysis | Newton methods | Estimates

Journal Article

Stochastic Processes and their Applications, ISSN 0304-4149, 05/2013, Volume 123, Issue 5, pp. 1563 - 1587

In this paper, Lp convergence and almost sure convergence of the Milstein approximation of a partial differential equation of advection–diffusion type driven...

Almost sure convergence | [formula omitted] convergence | Stochastic partial differential equation | Galerkin method | Finite Element method | Milstein scheme | Advection–diffusion equation | Backward Euler scheme | Advection-diffusion equation | convergence | Computational Mathematics | Lp convergence | Beräkningsmatematik | Sannolikhetsteori och statistik | Probability Theory and Statistics

Almost sure convergence | [formula omitted] convergence | Stochastic partial differential equation | Galerkin method | Finite Element method | Milstein scheme | Advection–diffusion equation | Backward Euler scheme | Advection-diffusion equation | convergence | Computational Mathematics | Lp convergence | Beräkningsmatematik | Sannolikhetsteori och statistik | Probability Theory and Statistics

Journal Article

ESAIM: Mathematical Modelling and Numerical Analysis, ISSN 0764-583X, 09/2016, Volume 50, Issue 5, pp. 1523 - 1560

We propose a space semi-discrete and a fully discrete finite element scheme for the modified phase field crystal equation (MPFC). The space discretization is...

Finite elements | Gradient-like systems | Second-order schemes | Łojasiewicz inequality | MATHEMATICS, APPLIED | MODELS | CAHN-HILLIARD EQUATION | DIFFERENCE SCHEME | BACKWARD EULER SCHEME | EQUILIBRIUM | GROWTH | Lojasiewicz inequality | second-order schemes | gradient-like systems | Finite element method | Galerkin method | Discretization | Computer simulation | Convergence

Finite elements | Gradient-like systems | Second-order schemes | Łojasiewicz inequality | MATHEMATICS, APPLIED | MODELS | CAHN-HILLIARD EQUATION | DIFFERENCE SCHEME | BACKWARD EULER SCHEME | EQUILIBRIUM | GROWTH | Lojasiewicz inequality | second-order schemes | gradient-like systems | Finite element method | Galerkin method | Discretization | Computer simulation | Convergence

Journal Article

EVOLUTION EQUATIONS AND CONTROL THEORY, ISSN 2163-2480, 06/2019, Volume 8, Issue 2, pp. 315 - 342

For initial value problems associated with operator-valued Riccati differential equations posed in the space of Hilbert-Schmidt operators existence of...

MATHEMATICS | MATHEMATICS, APPLIED | weak solution | backward Euler method | semi-definite data | well-posedness | convergence | Hilbert-Schmidt operator | Riccati differential equation | BOUNDARY CONTROL PROBLEM

MATHEMATICS | MATHEMATICS, APPLIED | weak solution | backward Euler method | semi-definite data | well-posedness | convergence | Hilbert-Schmidt operator | Riccati differential equation | BOUNDARY CONTROL PROBLEM

Journal Article

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Finite element method for two-dimensional space-fractional advection–dispersion equations

Applied Mathematics and Computation, ISSN 0096-3003, 04/2015, Volume 257, pp. 553 - 565

The backward Euler and Crank–Nicolson–Galerkin fully-discrete approximate schemes for two-dimensional space-fractional advection–dispersion equations are...

Finite element method | Space-fractional advection–dispersion equation | Crank–Nicolson–Galerkin scheme | Backward Euler scheme | Optimal error estimate | Crank-Nicolson-Galerkin scheme | Space-fractional advection-dispersion equation | SPECTRAL METHOD | MATHEMATICS, APPLIED | NUMERICAL-METHOD | ADOMIAN DECOMPOSITION | DIFFUSION | DIFFERENCE APPROXIMATIONS | Analysis | Methods | Operators | Approximation | Mathematical analysis | Projection | Mathematical models | Derivatives | Two dimensional | Optimization | Numerical Analysis | Mathematics

Finite element method | Space-fractional advection–dispersion equation | Crank–Nicolson–Galerkin scheme | Backward Euler scheme | Optimal error estimate | Crank-Nicolson-Galerkin scheme | Space-fractional advection-dispersion equation | SPECTRAL METHOD | MATHEMATICS, APPLIED | NUMERICAL-METHOD | ADOMIAN DECOMPOSITION | DIFFUSION | DIFFERENCE APPROXIMATIONS | Analysis | Methods | Operators | Approximation | Mathematical analysis | Projection | Mathematical models | Derivatives | Two dimensional | Optimization | Numerical Analysis | Mathematics

Journal Article

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