A system identification approach for developing and parameterising an agroforestry system model under constrained availability of data
Keesman, Karel J. | Graves, Anil | van Der Werf, Wopke | Burgess, Paul J. | Palma, Joao | Dupraz, Christian | van Keulen, Herman | Wageningen University and Research [Wageningen] (WUR) | School of Applied Sciences ; Cranfield University | Universidade Técnica de Lisboa (UTL) | Fonctionnement et conduite des Systèmes de culture Tropicaux et Méditerranéens ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro) | Plant Production Systems ; Wageningen University and Research [Wageningen] (WUR) | This research was carried out as part of the SAFE (Silvoarable Agroforestry for Europe) project funded by the EU under its Quality of Life programme, contract number QLF5-CT-2001-00560, and the support is gratefully acknowledged. We would also like to thank Klaas Metselaar for his early work on crop calibrations.
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Показать больше [+] Меньше [-]Английский. This paper introduces a system identification approach to overcome the problem of insufficient data when developing and parameterising an agroforestry system model. Typically, for these complex systems the number of available data points from actual systems is less than the number of parameters in a (process-based) model. In this paper, we follow a constrained parameter optimization approach, in which the constraints are found from literature or are given by experts. Given the limited a priori systems knowledge and very limited data sets, after decomposition of the parameter estimation problem and after model adaptation, we were able to produce an acceptable correspondence with validation data from a real-world agroforestry experiment
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