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- Title
Exploring stochasticity and imprecise knowledge based on linear inequality constraints.
- Authors
Subbey, Sam; Planque, Benjamin; Lindstrøm, Ulf
- Abstract
This paper explores the stochastic dynamics of a simple foodweb system using a network model that mimics interacting species in a biosystem. It is shown that the system can be described by a set of ordinary differential equations with real-valued uncertain parameters, which satisfy a set of linear inequality constraints. The constraints restrict the solution space to a bounded convex polytope. We present results from numerical experiments to show how the stochasticity and uncertainty characterizing the system can be captured by sampling the interior of the polytope with a prescribed probability rule, using the Hit-and-Run algorithm. The examples illustrate a parsimonious approach to modeling complex biosystems under vague knowledge.
- Subjects
CONVEX polytopes; DIFFERENTIAL equations; STOCHASTIC models; FOOD chains; MATHEMATICAL models; BIOLOGICAL systems
- Publication
Journal of Mathematical Biology, 2016, Vol 73, Issue 3, p575
- ISSN
0303-6812
- Publication type
Article
- DOI
10.1007/s00285-015-0959-z