An optimized Crank–Nicolson finite difference extrapolating model for the fractional-order parabolic-type sine-Gordon equation
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Title
An optimized Crank–Nicolson finite difference extrapolating model for the fractional-order parabolic-type sine-Gordon equation
Authors
Keywords
Proper orthogonal decomposition, Classical Crank–Nicolson finite difference model, Fractional-order parabolic-type sine-Gordon equation, Optimized Crank–Nicolson finite difference extrapolating model, Existence, stabilization, and convergence, 34K28, 35R11, 65M12
Journal
Advances in Difference Equations
Volume 2019, Issue 1, Pages -
Publisher
Springer Nature
Online
2019-01-03
DOI
10.1186/s13662-018-1939-6
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- (2017) Mehdi Dehghan et al. JOURNAL OF COMPUTATIONAL PHYSICS
- A POD-based-optimized finite difference CN-extrapolated implicit scheme for the 2D viscoelastic wave equation †
- (2017) Hong Xia et al. MATHEMATICAL METHODS IN THE APPLIED SCIENCES
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- A reduced finite element formulation based on POD method for two-dimensional solute transport problems
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- A reduced finite volume element formulation and numerical simulations based on POD for parabolic problems
- (2010) Zhendong Luo et al. JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
- Nonlinear Model Reduction via Discrete Empirical Interpolation
- (2010) Saifon Chaturantabut et al. SIAM JOURNAL ON SCIENTIFIC COMPUTING
- Some reduced finite difference schemes based on a proper orthogonal decomposition technique for parabolic equations
- (2009) Ping Sun et al. APPLIED NUMERICAL MATHEMATICS
- A reduced finite difference scheme based on singular value decomposition and proper orthogonal decomposition for Burgers equation
- (2008) Zhendong Luo et al. JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
- Mixed Finite Element Formulation and Error Estimates Based on Proper Orthogonal Decomposition for the Nonstationary Navier–Stokes Equations
- (2008) Zhendong Luo et al. SIAM JOURNAL ON NUMERICAL ANALYSIS
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