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Application of an evolutionary algorithm to the inverse parameter estimation of an individual-based model

TitleApplication of an evolutionary algorithm to the inverse parameter estimation of an individual-based model
Publication TypeJournal Article
Year of Publication2010
AuthorsDuboz, R, Versmisse, D, Travers, M, Ramat, E, Shin, Y-J
JournalEcological Modelling
Volume221
Pagination840–849
Date Publishedmar
ISSN0304-3800
KeywordsEvolutionary and genetic algorithms, Individual-based model, Marine ecosystem model, Model calibration, Parameter estimation
Abstract

Inverse parameter estimation of individual-based models ({IBMs}) is a research area which is still in its infancy, in a context where conventional statistical methods are not well suited to confront this type of models with data. In this paper, we propose an original evolutionary algorithm which is designed for the calibration of complex {IBMs}, i.e. characterized by high stochasticity, parameter uncertainty and numerous non-linear interactions between parameters and model output. Our algorithm corresponds to a variant of the population-based incremental learning ({PBIL}) genetic algorithm, with a specific “optimal individual” operator. The method is presented in detail and applied to the individual-based model {OSMOSE}. The performance of the algorithm is evaluated and estimated parameters are compared with an independent manual calibration. The results show that automated and convergent methods for inverse parameter estimation are a significant improvement to existing ad hoc methods for the calibration of {IBMs}.

URLhttp://www.sciencedirect.com/science/article/pii/S0304380009008102
DOI10.1016/j.ecolmodel.2009.11.023