System identification in production ecology: from theory to agroforestry practice
dc.contributor.author | Keesman, K. J. | - |
dc.contributor.author | Graves, Anil R. | - |
dc.contributor.author | van der Werf, Wopke | - |
dc.contributor.author | Burgess, Paul J. | - |
dc.date.accessioned | 2012-05-30T23:02:03Z | |
dc.date.available | 2012-05-30T23:02:03Z | |
dc.date.issued | 2009-07-08T00:00:00Z | - |
dc.description.abstract | This paper introduces a system identification approach to agricultural ecosystems. In particular, the identification of an agroforestry system, combining trees with crops, is subject of study. Typically, for these systems N < p, where N is the number of data points and p the number of parameters in a (process-based) model. In this paper, we follow a constrained 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 fit to validation data from a real-world agroforestry experiment. | en_UK |
dc.identifier.uri | http://dspace.lib.cranfield.ac.uk/handle/1826/5455 | |
dc.language.iso | en_UK | - |
dc.title | System identification in production ecology: from theory to agroforestry practice | en_UK |
dc.type | Conference paper | - |