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

Raphaël Duboz, David Versmisse, Morgane Travers, Eric Ramat and Yunne-Jai Shin

Ecological Modelling, 2010, vol. 221, issue 5, 840-849

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.

Keywords: Parameter estimation; Model calibration; Evolutionary and genetic algorithms; Individual-based model; Marine ecosystem model (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:221:y:2010:i:5:p:840-849

DOI: 10.1016/j.ecolmodel.2009.11.023

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