Abstract
In this paper a parameter identification algorithm is developed for particles models. The estimation problem is solved with a gradient based algorithm. For each generated particle track, the adjoint track is determined to efficiently compute the gradient of the criterion. The asymptotic behaviour of the algorithm for an increasing number of particles is discussed. Finally the approach is illustrated with an application.
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© 1994 Springer Science+Business Media Dordrecht
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Heemink, A.W., Van Den Boogaard, H.F.P. (1994). Identification of Stochastic Dispersion Models. In: Hipel, K.W. (eds) Stochastic and Statistical Methods in Hydrology and Environmental Engineering. Water Science and Technology Library, vol 10/4. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-1072-3_4
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DOI: https://doi.org/10.1007/978-94-011-1072-3_4
Publisher Name: Springer, Dordrecht
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