Learning ensembles of population dynamics models and their application to modelling aquatic ecosystems

Nikola Simidjievski, Ljupčo Todorovski and Sašo Džeroski

Ecological Modelling, 2015, vol. 306, issue C, 305-317

Abstract: Ensemble methods are machine learning methods that construct a set of models and combine their outputs into a single prediction. The models within an ensemble can have different structure and parameters and make diverse predictions. Ensembles achieve high predictive performance, benefiting from the diversity of the individual models and outperforming them.

Keywords: Aquatic ecosystems; Population dynamics; Phytoplankton growth; Process-based modelling; Ensembles; Bagging (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:306:y:2015:i:c:p:305-317

DOI: 10.1016/j.ecolmodel.2014.08.019

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