Global optimization approaches to parameters identification in immune competition model
Lebkir Afraites, Abdelghani Bellouquid · Communications in Applied and Industrial Mathematics · 2014
The identification of the parameters in a model of immune competition is treated in this paper. More precisely, an approach of inverse problems toward the identification from measurements of densities of cells population is used. The inverse problem is transferred into a parametric optimization problem using the nonlinear identification approach with a Least Square objective function. Global optimization techniques are pursued and a design procedure for global robust optimization is developed using the so-called Kriging method, optimization approaches are used to determine the global robust optimum of a surrogate model.