in this paper, solution of nonlinear optimal control problems and the controlled duffing oscillator, as a special class of optimal control problems, are considered and an efficient algorithm is proposed. this algorithm is based on state parametrization as a polynomial with unknown coefficients. by this method, the control and state variables can be approximated as a function of time. also, the ...

Optimal prediction is a method to approximate the average solution of a large system of ordinary differential equations by a smaller system. In this thesis we show how optimal prediction can be applied in the field of molecular dynamics in order to reduce the number of particles. We apply optimal prediction to a model problem describing a surface coating process and show how asymptotic methods ...

The article deals with the description of the conceptual and linguistic nature, the modus character and the field structure of the linguistic category of the approximation. It also deals with the analysis of the role of the inherent and adherent approximators as well as the context in the realization of the invariant meaning of the approximation in the German language. Pragmatic potential of th...

A classiier system, XCSF, is introduced in which the prediction estimation mechanism is used to learn approximations to functions. The addition of weight vectors to the classiiers allows piecewise-linear approximation, where the classiier's prediction is calculated instead of being a xed scalar. The weight vector and the classiier's condition co-adapt. Results on functions of up to six dimensio...

in this paper, we propose the chebyshev wavelet approximation for the numerical solution of a class of integro-differential equation which describes the charged particle motion for certain configurations of oscillating magnetic fields. we show that the chebyshev approximation transform an integral equation to an explicit system of linear algebraic equations. illustrative examples are included t...

We study relations between evidence theory and S-approximation spaces. Both theories have their roots in the analysis of Dempsterchr('39')s multivalued mappings and lower and upper probabilities, and have close relations to rough sets. We show that an S-approximation space, satisfying a monotonicity condition, can induce a natural belief structure which is a fundamental block in evidence theory...