Calibration of a crop simulation model using an evolutionary algorithm with self-adaptation | Zendy

Pierre Stratonovitch | Zendy; Mikhail A. Semenov | Zendy

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Calibration of a crop simulation model using an evolutionary algorithm with self-adaptation

Author(s) -

Pierre Stratonovitch,

Mikhail A. Semenov

Publication year - 2010

Publication title -

procedia - social and behavioral sciences

Language(s) - English

Resource type - Journals

ISSN - 1877-0428

DOI - 10.1016/j.sbspro.2010.05.210

Subject(s) - calibration , set (abstract data type) , adaptation (eye) , computer science , parameter space , evolutionary algorithm , algorithm , selection (genetic algorithm) , data set , mathematical optimization , mathematics , machine learning , artificial intelligence , statistics , biology , neuroscience , programming language

Calibration of cultivar parameters of a crop simulation model can represent a considerable challenge when observed data for a single cultivar is available for multiple environments. Calibration can be considered as a search of the optimal set of parameters in a multidimensional parameter space. An evolutionary algorithm with self-adaptation has been developed and applied to calibrate parameters of the Sirius crop simulation model for several experimental datasets

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