1 research outputs found
Data adaptation in HANDY economy-ideology model
The concept of mathematical modeling is widespread across almost all of the
fields of contemporary science and engineering. Because of the existing
necessity of predictions the behavior of natural phenomena, the researchers
develop more and more complex models. However, despite their ability to better
forecasting, the problem of an appropriate fitting ground truth data to those,
high-dimensional and nonlinear models seems to be inevitable. In order to deal
with this demanding problem the entire discipline of data assimilation has been
developed. Basing on the Human and Nature Dynamics (HANDY) model, we have
presented a detailed and comprehensive comparison of Approximate Bayesian
Computation (classic data assimilation method) and a novelty approach of
Supermodeling. Furthermore, with the usage of Sensitivity Analysis, we have
proposed the methodology to reduce the number of coupling coefficients between
submodels and as a consequence to increase the speed of the Supermodel
converging. In addition, we have demonstrated that usage of Approximate
Bayesian Computation method with the knowledge about parameters' sensitivities
could result with satisfactory estimation of the initial parameters. However,
we have also presented the mentioned methodology as unable to achieve similar
predictions to Approximate Bayesian Computation. Finally, we have proved that
Supermodeling with synchronization via the most sensitive variable could effect
with the better forecasting for chaotic as well as more stable systems than the
Approximate Bayesian Computation. What is more, we have proposed the adequate
methodologies.Comment: 172 page