Analysing and forecasting transitions in complex systems

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Title: Analysing and forecasting transitions in complex systems
Authors: Piovani, Duccio
Item Type: Thesis or dissertation
Publication Date: 2016-04-25T09:36:48Z
Abstract: We analyse in detail a new approach to the monitoring and forecasting of the onset of transitions in high dimensional complex systems by application to the Tangled Nature model of evolutionary ecology and high dimensional replicator systems with a stochastic element, the Stochastic Replicator model. A high dimensional stability matrix is derived for the mean field approximation to the stochastic dynamics. This allows us to determine the stability spectrum about the observed quasi-stable configurations. From overlap of the instantaneous configuration vector of the full stochastic system with the eigenvectors of the unstable directions of the deterministic mean field approximation we are able to construct a good early-warning indicator of the transitions occurring intermittently.
Content Version: Open Access
Issue Date: Sep-2015
Date Awarded: Mar-2016
Supervisor: Jensen, Henrik
Funder's Grant Number: CONGAS (Grant FP7-ICT-2011-8-317672)
Department: Mathematics
Publisher: Imperial College London
Qualification Level: Doctoral
Qualification Name: Doctor of Philosophy (PhD)
Appears in Collections:Mathematics PhD theses

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