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On auto-calibration algorithms for a forest growth simulation model

Man Jia / Shiying Tian / Gaolin Zheng
Published Online: 2011-12-27 | DOI: https://doi.org/10.2478/s13537-011-0026-9


Forest growth simulation models are useful in evaluating the effects of management practices and climate changes in terrestrial ecosystems, however their successful application requires accurate calibration of model parameters. We have implemented here a stepwise line search (SLS), Gibbs sampling (GS) and preclustering based strength Pareto algorithm (K-SPEA2) to find an optimal set of parameters.

Keywords: forest growth simulation model; calibration; Gibbs sampling; stepwise line search algorithm; strength Pareto evolutionary algorithm; multi-objective optimization

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About the article

Published Online: 2011-12-27

Published in Print: 2011-12-01

Citation Information: Open Computer Science, Volume 1, Issue 4, Pages 367–374, ISSN (Online) 2299-1093, DOI: https://doi.org/10.2478/s13537-011-0026-9.

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© 2011 Versita Warsaw. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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