Fuzzy auto-regressive model and its applications

Author

Ozawa, Kazuhiro ; Watanabe, Takumi ; Kanke, Masayasu

Author_Institution

Fac. of Econ., Hosei Univ., Japan

Volume

1

fYear

1997

fDate

27-23 May 1997

Firstpage

112

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

Keywords

autoregressive processes; economics; forecasting theory; fuzzy logic; linear programming; parameter estimation; time series; Japanese worker household; estimation; forecasting data; fuzzy auto-regressive model; identification; linear programming; living expenditure; model parameters; objective function; optimization; price index fuzzy time series; Economic forecasting; Linear programming; Power generation economics; Power system modeling; Production facilities; Regression analysis; Stochastic processes; Testing; Time series analysis; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Knowledge-Based Intelligent Electronic Systems, 1997. KES '97. Proceedings., 1997 First International Conference on

Conference_Location

Adelaide, SA

Print_ISBN

0-7803-3755-7

Type

conf

DOI

10.1109/KES.1997.616865

Filename

616865