Prediction of Boiler Output Variables Through the PLS Linear Regression Technique

‎ Prediction of Boiler Output Variables Through ‎
the PLS Linear Regression Technique

   Abdelmalek Kouadri1, Mimoun Zelmat1, and AlHussein Albarbar2‎
‎1Applied Control Laboratory, University of Boumerdes, Algeria
‎2Department of Engineering and Technology, Manchester Metropolitan University, 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.‎

 
Received November 26, 2008; accepted May 17, 2009‎

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