Insight of the fuzzy grey autoregressive model

In our previous research, we proposed a fuzzy grey regression model for solving limited time series data. The present paper follows the previous research and proposes a fuzzy grey autoregressive model for considering that the current value is correlated with previous values. The proposed model combines the advantages of the grey system model, the fuzzy regression model and the autoregressive model. Two illustrated examples are provided in which the amount of internet subscribers in Taiwan and the global demand of LCD TVs are forecasted. The results of these practical applications show that the proposed model can be used to obtain smaller forecasting errors of MAPE and RMSE, and that it makes good forecasts for the next demand period of internet subscribers and LCD TV. Furthermore, this model makes it possible for decision makers to forecast the best and the worst estimates based on fewer observations.

[1]  James J. Buckley,et al.  Monte Carlo methods in fuzzy linear regression II , 2007, Soft Comput..

[2]  Hsiao-Fan Wang,et al.  Insight of a fuzzy regression model , 2000, Fuzzy Sets Syst..

[3]  Hung T. Nguyen,et al.  Fuzzy time series analysis and forecasting , 2006 .

[4]  Chin-Tsai Lin,et al.  Forecast of the output value of Taiwan's opto-electronics industry using the Grey forecasting model , 2003 .

[5]  James J. Buckley,et al.  Monte Carlo methods in fuzzy linear regression , 2007, Soft Comput..

[6]  H. Moskowitz,et al.  Fuzzy versus statistical linear regression , 1996 .

[7]  Chia-Yon Chen,et al.  Applications of improved grey prediction model for power demand forecasting , 2003 .

[8]  Gwilym M. Jenkins,et al.  Time series analysis, forecasting and control , 1971 .

[9]  Ruey-Chyn Tsaur,et al.  Extrapolating internet users in Taiwan by risk assessment , 2003 .

[10]  Masatake Nagai,et al.  A GM(1,1)–Markov chain combined model with an application to predict the number of Chinese international airlines , 2007 .

[11]  Piero Risoluti.  Fuzzy Sets, Decision Making, and Expert Systems , 2004 .

[12]  Ruey-Chyn Tsaur,et al.  Fuzzy Regression for Seasonal Time Series Analysis , 2002, Int. J. Inf. Technol. Decis. Mak..

[13]  George E. P. Box,et al.  Time Series Analysis: Forecasting and Control , 1977 .

[14]  J. Deng,et al.  Introduction to Grey system theory , 1989 .

[15]  Hideo Tanaka,et al.  A LINEAR REGRESSION MODEL WITH FUZZY FUNCTIONS , 1982 .

[16]  J. Kacprzyk,et al.  Fuzzy regression analysis , 1992 .

[17]  Chun-I Chen,et al.  Application of the novel nonlinear grey Bernoulli model for forecasting unemployment rate , 2008 .

[18]  Ping-Teng Chang,et al.  Fuzzy seasonality forecasting , 1997, Fuzzy Sets Syst..

[19]  Ruey-Chyn Tsaur.  Forecasting analysis by using fuzzy grey regression model for solving limited time series data , 2008, Soft Comput..

[20]  Yi-Chun Liao,et al.  Forecasting LCD TV Demand Using the Fuzzy Grey Model Gm(1, 1) , 2007, Int. J. Uncertain. Fuzziness Knowl. Based Syst..