ARIMA models versus gene expression programming in precipitation modeling
Alina Bărbulescu, Elena Bãutu · 2009
In this paper we present a case study: the application of some conceptually different approaches to the problem of identifying a model for a hydrological time series. The problem is particularly challenging, due to the size of the time series and more importantly, to the many complex phenomena that influence such time series and that reflect in the characteristics of the data. We use well established statistical methods to detect change points in the time series, and we model the subseries obtained by ARIMA, GEP and the adaptive variant and a combination of the two. The models obtained state the efficiency of combining pure statistical tests and methods with heuristic approaches.