Parameter inversion estimation in photosynthetic models: Impact of different simulation methods

• DOI: 10.1007/s11099-014-0027-8
• Publication Date: 2014-05-13T09:09:51Z
• Authors: H. B. Wang; M. G. Ma; Y. M. Xie; X. F. Wang; J. Wang
• Keywords: Control variable

When we apply ecological models in environmental management, must assess the accuracy of parameter estimation and its impact on model predictions. Parameters estimated by conventional techniques tend to be nonrobust require excessive computational resources. However, optimization algorithms are highly robust generally exhibit convergence inversion with nonlinear models. They can simultaneously generate a large number estimates using an entire data set. In this study, tested four (simulated annealing, shuffled complex evolution, particle swarm optimization, genetic algorithm) optimize parameters photosynthetic depending different temperatures. We investigated if boundary values control variables influenced efficiency various obtained optimal solutions all bounds were constrained properly. processing time use varied obtained. addition, temperature dependence formalization impacted optimally process. found that peaked response provided best fit data.