Anais do Simpósio Brasileiro de Pesquisa Operacional
Anais do Simpósio Brasileiro de Pesquisa Operacional

El Niño Southern Oscillation (ENSO) events have a significant impact on the global climate, leading to various consequences such as droughts. These events are loosely intertwined with multiple aspects of health, agriculture, and economics. Therefore, accurate forecasting of ENSO events is crucial in mitigating their impacts. In recent literature, multiple predictor systems (MPS) methods, including Dynamic Ensemble Selection (DES), have gained prominence due to their ability to enhance overall forecasting accuracy. However, despite being a promising alternative, there is a lack of studies focusing on ENSO-related time series forecasting using DES methods. Hence, this research aims to analyze the performance of a DES method in one-step ahead forecasting of the Oceanic Niño Index (ONI) time series. Based on the presented results, the DES method demonstrated superior performance compared to the alternative methods implemented in this study across the established performance measures.