ICCIMA '05 Proceedings of the Sixth International Conference on Computational Intelligence and Multimedia Applications
State and parameter estimation for nonlinear biological phenomena modeled by S-systems
Digital Signal Processing
Hi-index | 0.00 |
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 parameters to a nonlinear changing strategy, the convergence speed of the proposed adaptive PSO has been accelerated. This project also describes the comparisons of different optimization methods' performances to understand how PSO may provide the best results.