A methodology based on the fuzzy identification for a hybrid method in times series forecasting models
Jose Gracildo Carvalho Júnior, Carlos Tavares da Costa, João Caldas do Lago Neto, Sandro Dimy Barbosa Bitar · OBSERVATÓRIO DE LA ECONOMÍA LATINOAMERICANA · 2024
This work presents a hybrid forecasting method, with concept and improvement through the fuzzy set’s theory coupled with the classic time series method. This study also proposed an identification tool that has not been published in the scientific literature for parametric point identification and estimation within the classical time series methodology combined with fuzzy sets theory, which generated a hybrid identification technique in fuzzy time data. In comparison to the forecasting methods consolidated in the literature, the results presented by the proposed method have been considered fully satisfactory due to the minimal error observed.