Copulas-based ensemble of Artificial Neural Networks for forecasting real world time series

Abstract

Time series combined forecasters have been superior to the respective single models in statistical terms. In this way, the linear combination functions, e.g. the simple average (SA) and the minimal variance (MV) approaches, have been the main alternatives for aggregation in the literature. In this work, it is proposed a copulas-based method for combining… (More)
DOI: 10.1109/IJCNN.2016.7727732

Topics

7 Figures and Tables

Cite this paper

@article{Oliveira2016CopulasbasedEO, title={Copulas-based ensemble of Artificial Neural Networks for forecasting real world time series}, author={Ricardo T. A. de Oliveira and Thaize Fernandes O. de Assis and Paulo Renato A. Firmino and Tiago Alessandro Esp{\'i}nola Ferreira and Adriano Lorena In{\'a}cio de Oliveira}, journal={2016 International Joint Conference on Neural Networks (IJCNN)}, year={2016}, pages={4089-4096} }