Title of article :
Prediction of Boiler Output Variables Through the PLS Linear Regression Technique
Author/Authors :
Kouadri, Abdelmalek University of Boumerdes - Applied Control Laboratory, Algeria , Zelmat, Mimoun University of Boumerdes - Applied Control Laboratory, Algeria , Albarbar, AlHussein Manchester Metropolitan University - Department of Engineering and Technology, UK
Abstract :
In this work, we propose to use the linear regression partial least square method to predict the output variables of the RA1G boiler. This method consists in finding the regression of an output block regarding an input block. These two blocks represent the outputs and inputs of the process. A criterion of cross validation, based on the calculation of the predicted residual sum of squares, is used to select the components of the model in the partial least square regression. The obtained results illustrate the effectiveness of this method for prediction purposes
Keywords :
Partial least square , principal component analysis , principal component regression , covariance , predicted residual sum of squares
Journal title :
The International Arab Journal of Information Technology (IAJIT)
Journal title :
The International Arab Journal of Information Technology (IAJIT)
