Forecasting time series by an ensemble of Artificial Neural Networks based on transforming the time series

Times series forecasting issue can be found in several subject areas as finance and business (e.g. foreign exchange rates, data for prices), industry (energy load and demand), climate and meteorology (e.g. sea surface temperature and El Nio phenomenon), health (e.g. prognosis from medical data) and many others. This paper is focused in univariate time series (x 1 , x 2 , …, x t ), so unknown future values are obtain from k previous (and known) values, i.e. x t+h = ƒ(x t , …, x t−k+1 ).