The Effect of Spatial Scale on Predicting Time Series: A Study on Epidemiological System Identification


Autoria(s): MONTEIRO, L. H. A.; OLIVEIRA, D. N.; CHAUI-BERLINCK, J. G.
Contribuinte(s)

UNIVERSIDADE DE SÃO PAULO

Data(s)

17/04/2012

17/04/2012

2009

Resumo

A susceptible-infective-recovered (SIR) epidemiological model based on probabilistic cellular automaton (PCA) is employed for simulating the temporal evolution of the registered cases of chickenpox in Arizona, USA, between 1994 and 2004. At each time step, every individual is in one of the states S, I, or R. The parameters of this model are the probabilities of each individual (each cell forming the PCA lattice ) passing from a state to another state. Here, the values of these probabilities are identified by using a genetic algorithm. If nonrealistic values are allowed to the parameters, the predictions present better agreement with the historical series than if they are forced to present realistic values. A discussion about how the size of the PCA lattice affects the quality of the model predictions is presented. Copyright (C) 2009 L. H. A. Monteiro et al.

CNPq

Identificador

MATHEMATICAL PROBLEMS IN ENGINEERING, 2009

1024-123X

http://producao.usp.br/handle/BDPI/14706

10.1155/2009/137854

http://dx.doi.org/10.1155/2009/137854

Idioma(s)

eng

Publicador

HINDAWI PUBLISHING CORPORATION

Relação

Mathematical Problems in Engineering

Direitos

openAccess

Copyright HINDAWI PUBLISHING CORPORATION

Palavras-Chave #CELLULAR-AUTOMATA #DYNAMICS #PATTERN #Engineering, Multidisciplinary #Mathematics, Interdisciplinary Applications
Tipo

article

original article

publishedVersion