Fuzzy Autoregressive Model using Real Time Series Data and Its Example of Application

Abstract

The autocorrelated fuzzy time series model uses fuzzy time series data to output fuzzy predictions. Since fuzzy operations are used to compute the fuzzy numbers, the vagueness of this model can be large. Therefore, a fuzzy autoregressive model using real time series data has been proposed. The proposed model was easy to use and the prediction accuracy was good in the numerical examples. A consumer price index was analyzed as an example of the application of the proposed model, the usefulness of the proposed model was confirmed. Then, the results are reported in this paper.