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We consider the problem of large-scale parameter estimations in nonlinear dynamic models of biochemical systems. In this work, the particle swarm optimization (PSO) method is adapted for estimation of model parameters in highly nonlinear, large-scale metabolic networks in systems biology. PSO is a recently developed novel metaheuristic optimization method. And with the modification of the essential...
In this work, the particle swarm optimization (PSO) algorithm combined with chaotic theory was employed to modeling data of biochemical systems. For this purpose, three case studies will be applied with PSO as parameter estimation problems and examine the performance of the new developed methodology.
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