Parameter estimation in a nonlinear dynamic model of an aquatic ecosystem with meta-heuristic optimization

► We estimate parameters in a nonlinear dynamic model of the Lake Bled ecosystem. ► We compare global meta-heuristics and local search for parameter estimation. ► Meta-heuristics yield models with lower error from both artificial and real data. ► Differential evolution is the best meta-heuristic (and converges faster). ► Within parameter estimation, the use of full simulation is better on real data.