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Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/3243

Title: Parametric identification of the model with one predator and two prey species
Authors: Shatalov, M
Greeff, JC
Joubert, SV
Fedotov, I
Keywords: Parametric models
Lion population
Coefficients
Inverse method
Statistical methods
Buffelspoort TIME 2008
Technology and its Integration into Mathematics Education Conference
TIME
Issue Date: Sep-2008
Publisher: Buffelspoort TIME 2008 Peer-reviewed Conference Proceedings
Citation: Shatalov, M, Greeff, JC, Fedotov, I and Joubert, SV. 2008. Parametric identification of the model with one predator and two prey species. Technology and its Integration into Mathematics Education Conference (TIME). Buffelspoort, South Africa, 22 - 26 September 2008, pp 101-109
Abstract: In this paper a mathematical model describing the interaction of a lion population with that of the zebra and wildebeest populations is considered. The traditional method uses a model with known coefficients and a CAS numerical routine to determine a numerical solution that can be compared to historical data about the populations. The numerical values of the coefficients involved are usually "educated guesses" made by the team consisting of, for example, biologists, game rangers and experienced applied mathematicians. The coefficients are usually described in terms of quantities such as "carrying capacity", "birth rate" et cetera, and might mean little to the mathematician. In this paper an "inverse method" is considered, that is, a method easy enough for senior undergraduate and graduate mathematics majors to understand and apply as part of a "biomechanics" team in the field. This approach considers the model in question to have unknown coefficients. Using a CAS, numerical integration is applied using the historical data and then elementary statistical methods are used to determine the value of the coefficients
Description: Buffelspoort TIME2008 Peer-reviewed Conference Proceedings, 22 – 26 September
URI: http://hdl.handle.net/10204/3243
ISBN: 9780620434546
Appears in Collections:Advanced mathematical modelling and simulation
General science, engineering & technology

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