Wind Power Prediction Based on Nonlinear Partial Least Square

Partial Least Square Discriminant Analysis for bankruptcy prediction

Wind Power Prediction Considering Nonlinear Atmospheric Disturbances

This paper considers the effect of nonlinear atmospheric disturbances on wind power prediction. A Lorenz system is introduced as an atmospheric disturbance model. Three new improved wind forecasting models combined with a Lorenz comprehensive disturbance are put forward in this study. Firstly, we define the form of the Lorenz disturbance variable and the wind speed perturbation formula. Then, d...

On the linear least-square prediction problem

An efficient algorithm is derived for the recursive computation of the filtering and all types of linear leastsquare prediction estimates (fixed-point, fixed-interval, and fixed-lead predictors) of a nonstationary signal vector. It is assumed that the signal is observed in the presence of an additive white noise which can be correlated with the signal. The methodology employed only requires tha...

Partial least squares methods: partial least squares correlation and partial least square regression.

Partial least square (PLS) methods (also sometimes called projection to latent structures) relate the information present in two data tables that collect measurements on the same set of observations. PLS methods proceed by deriving latent variables which are (optimal) linear combinations of the variables of a data table. When the goal is to find the shared information between two tables, the ap...

Seepage with Nonlinear Permeability by Least Square FEM

In seepage problems, the coefficients of permeability in Laplace equation are usually assumed to be constant vs. both space and time; but in reality these coefficients are variable. In this study, the effect of material deformation due to external loads (consolidation) and variation of head in the consolidation process are considered. For the first case, formulation of kx and ky can be defined ...