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
From page
260
To page
264
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)
Record number
2543573
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