This paper indicates the application of the Homotopy-WHEP method to find an approximate for the statistical moments of the stochastic solution processes of 2-D Navier-Stokes equations under the effect of a stochastic excitation. Some cases studies from the results of this method are considered to illustrate some corrections.

Collocation method using quintic B-splines finite element have been developed for solving numerically the Hirota-Satsuma coupled MKdV equation. Accuracy of the proposed method is shown numerically by calculating conservation laws, L_2 and L_∞ norms on studying of a soliton solution. It is shown that the collocation scheme for solutions of the MKdV equation gives rise to smaller errors and is quite easy to implement. Numerical experiments support these theoretical results.

In this paper, a high-gain output feedback control structure is applied in order to be optimized with GA for a MIMO nonlinear model of a flight object. In control structure, a modified GA algorithm for obtaining a suitable measurement matrix in feedback loop is proposed which minimizes the interaction between the outputs. The proposed method has two major advantages in compare to other methods; first of all, the proposed method is independent of system degree or system complexity and secondly, in this method some of unknown high-gain method parameters such as arbitrary diagonal matrix, etc are discarded. Computer simulations are carried out for showing the performance of the designed controller against common high-gain controller.

A Poisson model typically is assumed for count data. It is assumed to have the same value for expectation and variance in a Poisson distribution, but most of the time there is over-dispersion in the model. Furthermore, the response variable in such cases is truncated for some outliers or large values. In this paper, a Poisson regression model is introduced on truncated data. In this model, we consider a response variable and one or more than one explanatory variables. The estimation of regression parameters using the maximum likelihood method is discussed and the goodness-of-fit for the regression model is examined. We study the effects of truncation in terms of parameters estimation and their standard errors via real data.