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BEGIN:VEVENT
DTSTAMP:20260409T120600Z
DTSTART;VALUE=DATE-TIME:20131002T130000
DTEND;VALUE=DATE-TIME:20131002T140000
SUMMARY:Complexity Forum: Andrey Morozov (Leicester)
TZID:Europe/London
UID:20131002-094d43a23d3fbe05013d8c399d5c247e@warwick.ac.uk
CREATED:20130321T091228Z
DESCRIPTION:Speaker: Andrey Morozov (Leicester) Title: Detecting structur
 al sensitivity in biological models: developing a new framework Abstract
 : When we construct mathematical models to represent a given real-world 
 system\, there is always a degree of uncertainty with regards to the mod
 el specification\, whether with respect to the choice of parameters or t
 o the choice of formulation of model functions. This can become a real p
 roblem in some cases\, where choosing two different functions with close
  shapes in a model can result in substantially different model predictio
 ns. This phenomenon is known as structural sensitivity\, and is a signif
 icant obstacle to improving the predictive power of models\, particularl
 y in fields where it is not possible to derive the functions suitable fo
 r representing system processes from theory or physical laws\, such as t
 he biological sciences. In this talk\, I shall revisit the notion of str
 uctural sensitivity and its relation to the property of structural (in)s
 tability\, and propose a general approach to reveal structural sensitivi
 ty which is a far more powerful technique than the conventional approach
  consisting of fixing a particular functional form and varying its param
 eters\, since we consider the infinite-dimensional neighbourhood of a gi
 ven model's unknown functions. In particular\, a rigorous method to unea
 rth sensitivity with respect to the local stability of a system's equili
 brium points will be discussed. Then\, I implement the method to explore
  sensitivity in several well-known multicomponent ecological models\, de
 monstrate the existence of structural sensitivity in these models and sh
 ow that conventional methods based on variation of parameters alone will
  often miss such sensitivity. I shall discuss the consequences that stru
 ctural sensitivity and the resulting model uncertainty may have for the 
 modelling of biological systems. In particular\, I shall consider that s
 tructural sensitivity may allow models to represent far more complex dyn
 amics than the dimension of the state-space may suggest\, and that in a 
 structurally sensitive model\, the concept of a "concrete" bifurcation s
 tructure may no longer be relevant. In this case\, we can only describe 
 bifurcations with a certain probability. I suggest several ways to defin
 e the probability of a bifurcation taking place when there is uncertaint
 y in the parameterization in model functions. I call bifurcations in suc
 h systems the fuzzy bifurcations and I provide an example of constructio
 n of a fuzzy bifurcation for a class of predator-prey biological models.
 
LOCATION:D1.07
CATEGORIES:forum
LAST-MODIFIED:20130321T091338Z
ORGANIZER;CN=Karen McKinley:
END:VEVENT
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