FORECASTING IN FUZZY SYSTEMS

Hsiao-Fan Wang () and Ruey-Chyn Tsaur ()
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Hsiao-Fan Wang: Department of Industry Engineering and Engineering Management, National Tsing Hua University, 101, Section 2, Kuang-Fu Road, Hsinchu, Taiwan, R.O.C.
Ruey-Chyn Tsaur: Department of Management Sciences and Decision Making, Tamkang University, No.151, Ying-Chuan Road, Tamsui, Taipei, Taiwan, R.O.C.

International Journal of Information Technology & Decision Making (IJITDM), 2011, vol. 10, issue 02, pages 333-352

Abstract: Fuzzy regression has been applied to marketing, management, and sales forecasting for many years. In this paper, two types of forecasting methods within the framework of fuzzy regression analysis are discussed. The first type is a conventional forecasting method, which intends to find the value of a dependent variable when the given values of independent variables are beyond the range covered by historical data. The second type considers forecasting in which the necessary values of independent variables are desired when the given value of a dependent variable does not fall within the range of historical data. While the first type can be applied in planning, the second one is useful for control and management. Numerical examples are provided for illustration.

Keywords: Fuzzy linear regression; forecasting; extrapolation; independent variable; dependent variable (search for similar items in EconPapers)
Date: 2011
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