IJPAM: Volume 52, No. 2 (2009)

AND ITS PARAMETER IDENTIFICATION





Faculty of Science
Mahidol University
Bangkok, 10400, THAILAND


Curtin University of Technology
Perth, WA6845, AUSTRALIA
e-mail: yhwu@maths.curtin.edu.au

Faculty of Science
Mahidol University
Bangkok, 10400, THAILAND
e-mail: scimt@mahidol.ac.th
Abstract.In this paper, we first propose a pandemic influenza
susceptib-le-exposed-infected-quarantined-recovered () model and analyze the model properties.
We then introduce a differential
evolution (DE) algorithm for determining the numerical values of the parameters
in the model. For a given set of measured data, e.g. from the first outbreak,
all the values of the model parameters can be determined by the algorithm. We have
also shown from numerical simulations that the DE algorithm yields the same parameter
values for different sets of initial guesses.
With the values of the parameters determined, the model can then be used
to capture the behavior of the next outbreaks of the disease. The
work provides an effective tool for predicting the spread of the
disease.
Received: March 10, 2009
AMS Subject Classification: 03C98
Key Words and Phrases: model, influenza pandemic, stability, differential evolution algorithm
Source: International Journal of Pure and Applied Mathematics
ISSN: 1311-8080
Year: 2009
Volume: 52
Issue: 2