A new pbkp_rediction approach of the COVID-19 virus pandemic behavior with a hybrid ensemble modular nonlinear autoregressive neural network

Abstract:

We describe in this paper an approach for pbkp_redicting the COVID-19 time series in the world using a hybrid ensemble modular neural network, which combines nonlinear autoregressive neural networks. At the level of the modular neural network, which is formed with several modules (ensembles in this case), the modules are designed to be efficient pbkp_redictors for each country. In this case, an integrator is used to combine the outputs of the modules, in this way achieving the goal of pbkp_redicting a set of countries. At the level of the ensembles, forming a part of the modular network, these are constituted by a set of modules, which are nonlinear autoregressive neural networks that are designed to be efficient pbkp_redictors under particular conditions for each country. In each ensemble, the results of the modules are combined with an aggregator to achieve a better and improved result for the ensemble. Publicly available …

Año de publicación:

2020

Keywords:

Fuente:

google