Multi-resolution Time–Series Prediction
Using Fuzzy Inductive Reasoning
Abstract
The paper describes a new approach to multiresolution prediction
of time series using Fuzzy Inductive Reasoning (FIR). The
time series is decomposed into a trend series and another series
describing the deviation from the trend. The two time series are
then predicted independently of each other, and the two predictions
are superposed in the end. The trend series is obtained by means of
a moving average, whereas the deviation series is obtained by a
process of de-trending using “daily return” calculations. The paper
deals both with interpolation and with extrapolation problems.
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Last modified: June 17, 2005 -- © François Cellier