Research On Parameter Identification For A Class Of Nonlinear Biochemical Systems

The rapid development of systems biology has been driven by the advances inexperimental methods which through mathematical model to study on detail andprinciple of the systems. It is still one of the major challenges in using time-course datato obtain parameters in this field of parameters estimation for nonlinear biochemicalsystems.This paper mainly studies the parameter identification for a class of nonlinearbiochemical systems in S-system. Most of the previous researchers have achievedsome achievements, but all those need very long time. In order to save CPU time, anew optimization model and a new optimization algorithm are presented to identify theparameters for nonlinear biochemical systems in S-system.The main content and results obtained of thesis are as follows:1. For a class of nonlinear biochemical systems in S-system, an optimizationmodel of parameter identification for nonlinear biochemical system model in S-systemis built, which is based on the least-square error criterion and the slop error criterion ofmetabolites, and then sequential quadratic programming algorithm is used to identifythe parameters of the optimization model to find a global solution.2. In order to illustrate the effectiveness of the algorithm proposed in this paper,the new model and algorithm are applied to several nonlinear biochemical systems.The results of simulation show that the algorithm proposed in this paper not only canobtain the approximate parameters of the model, but also can save CPU time.