This thesis demonstrated how the Newton and BFGS algorithm could be used to solve the standard VGM relations and least-squares formulation respectively, for arbitrary forms of the _ parameter, including nonlinear _ s, appearing in the VMM. The proposed procedure were also shown to be able to handle arbitrary projectors that are compatible with the VGM. When applied to the advection-di_usion equation, Burgers' equation and Stokes equations the algorithms always reached the speci_ed stopping criteria and did not exceed the maximum alloted iterations. Additionally the increase in computational e_ort required was shown to be limited. However, it was shown that the Newton procedure for the VGM could not be used in cases where the local VGM resid...
The Minimizing Movement (MM) scheme is a variational method introduced by E. De Giorgi to solve grad...
The rapid development of artificial intelligence and computational sciences has attracted much more ...
Many methods for solving minimization problems are variants of Newton method, which requires the spe...
The Variational Germano Identity [1, 2] is used to optimize the coefficients of residual-based subgr...
Parameters for SGS models within the variational multiscale method for the Stokes equations are dete...
In this chapter the recently introduced Variational Germano procedure is revisited. The procedure is...
To solve an unconstrained nonlinear minimization problem, we propose an optimal algorithm (OA) as we...
The maximum likelihood method is usually chosen to estimate the regression parameters of Generalized...
AbstractQuasi-Newton methods for unconstrained minimization generate a sequence of matrices that can...
this paper we extend the algorithm to a scaled gradient projection. The diagonal scaling matrix appr...
In this paper the recently introduced Variational Germano procedure is revisited. The procedure is e...
The BFGS method is one of the most effective quasi-Newton algorithms for minimization-optimization p...
AbstractA bound on the possible deterioration in the condition number of the inverse Hessian approxi...
In displacement oriented methods of structural mechanics may static and dynamic equilibrium conditio...
International audienceThis paper investigates the capability of a Quasi-Newton optimization algorith...
The Minimizing Movement (MM) scheme is a variational method introduced by E. De Giorgi to solve grad...
The rapid development of artificial intelligence and computational sciences has attracted much more ...
Many methods for solving minimization problems are variants of Newton method, which requires the spe...
The Variational Germano Identity [1, 2] is used to optimize the coefficients of residual-based subgr...
Parameters for SGS models within the variational multiscale method for the Stokes equations are dete...
In this chapter the recently introduced Variational Germano procedure is revisited. The procedure is...
To solve an unconstrained nonlinear minimization problem, we propose an optimal algorithm (OA) as we...
The maximum likelihood method is usually chosen to estimate the regression parameters of Generalized...
AbstractQuasi-Newton methods for unconstrained minimization generate a sequence of matrices that can...
this paper we extend the algorithm to a scaled gradient projection. The diagonal scaling matrix appr...
In this paper the recently introduced Variational Germano procedure is revisited. The procedure is e...
The BFGS method is one of the most effective quasi-Newton algorithms for minimization-optimization p...
AbstractA bound on the possible deterioration in the condition number of the inverse Hessian approxi...
In displacement oriented methods of structural mechanics may static and dynamic equilibrium conditio...
International audienceThis paper investigates the capability of a Quasi-Newton optimization algorith...
The Minimizing Movement (MM) scheme is a variational method introduced by E. De Giorgi to solve grad...
The rapid development of artificial intelligence and computational sciences has attracted much more ...
Many methods for solving minimization problems are variants of Newton method, which requires the spe...