Soft sensor for polypropylene melt index based on improved orthogonal least squares

Abstract

A new method to build melt index soft sensor is proposed based on improved orthogonal least squares (IOLS) for nonlinear polypropylene process. OLS model has good generalization and sparseness by combining parameter local regularization and leave-one-out mean square error in cost function. Orthogonal signal correction(OSC) is applied to preprocess OLS model… (More)

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