Fuzzy auto-regressive model and its applications

Abstract

The authors propose the fuzzy auto-regressive (AR) model and its applications. The identification and the estimation of the model and the model parameters are optimized by linear programming. The performance of the proposed model has already been tested by random data. They first propose an improved fuzzy AR model. The point of difference of the previous method is the objective function of the optimization. This method is applied to forecasting data of the living expenditure of a worker's household in Japan, and price index fuzzy time series. To use the fuzzy AR model, one can describe the behavior of fuzzy time series which cannot be described by the stochastic model.