Parameter estimation for crop growth model using evolutionary and bio-inspired algorithms
An approach based on evolutionary and bio-inspired algorithms is proposed for solving the parameter estimation problem in crop growth dynamic models. Differential Evolution algorithm showed the best performance in solving the parameter estimation problem of a dynamic crop growth model. A statistical analysis and ANOVA were applied to quantitatively evaluate the efficiency and effectiveness of Differential Evolution, CMA-ES, PSO, ABC and LSE algorithms.
parameter estimation bio-inspired algorithms evolutionary algorithms sucros model