This paper will concentrate on contributions of CWI to the development of parallel Runge-Kutta (RK) methods. We shall describe two approaches to construct such methods. In both approaches, a conventional implicit RK method is used as a corrector equation whose solution is approximated by an iterative method. In the first approach, the iteration method uses a fixed number of iterations without s...

A new, more accurate Hessian-based predictor-corrector algorithm has been developed for simulating classical trajectories of molecules in intense laser fields. The first and second derivatives of the gradient with respect to the electric field are included in the both the predictor and the corrector steps for integrating trajectories. A Taylor expansion of the gradient is used as the surface fo...

in this paper, we study the numerical solution of hybrid fuzzy differential equations by using differential transformation method (dtm). this is powerful method which consider the approximate solution of a nonlinear equation as an infinite series usually converging to the accurate solution. several numerical examples are given and by comparing the numerical results obtained from dtm  and  predi...

A class of one-step methods which obtain a block of r new values at each step are studied. The asymptotic behavior of both implicit and predictor-corrector procedures is examined.

In this paper we study numerical methods for hybrid fuzzy differential equations by an application of the Adams fifth order predictor-corrector method for fuzzy differential equations. We prove a convergence result and give numerical examples to illustrate the theory.

Laboratory experimental data is often erroneous. This error is more apparent in data obtained from testing of anisotropic composite materials such as masonry wall panels. In this paper data colleted from the laboratory tests of masonry panels is presented. Methodologies for reducing (correcting) error in laboratory tested data are discussed. The concept of stiffness/strength corrector to model ...

This paper deals with set membership state estimation for continuous-time systems from discrete-time measurements, in the unknown but bounded error framework. The classical predictor-corrector approach to state estimation uses interval Taylor methods for solving the prediction phase, which are known to have poor performance in presence of large model or input uncertainty. In this paper, we show...