Original scientific paper

The Fuzzy Logic Method for Simpler Forecasting

Jeffrey E. Jarrett ; University of Rhode Island
Jeffrey S. Plouffe ; University of Rhode Island

Abstract

Fildes and Makridakis (1998), Makridakis and
Hibon (2000), and Fildes (2001) indicate that simple
extrapolative forecasting methods that are robust forecast
equally as well or better than more complicated methods,
i.e. Box‐Jenkins and other methods.
We study the Direct Set Assignment (DSA) extrapolative
forecasting method. The DSA method is a non‐linear
extrapolative forecasting method developed within the
Mamdani Development Framework, and designed to
mimic the architecture of a fuzzy logic control system.
We combine the DSA method Winters’ Exponential
smoothing. This combination provides the best observed
forecast accuracy in seven of nine subcategories of time
series, and is the top three in terms of observed accuracy
in two subcategories. Hence, fuzzy logic which is the
basis of the DSA method often is the best method for
forecasting.

Keywords

Hrčak ID:

71513

URI

https://hrcak.srce.hr/71513

Publication date:

15.8.2011.

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