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Analysis of pseudo‐periodic chronological series with irregularly time‐spaced data in view to their prediction. IV. Using a symbolic learning method

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  • Joël Quinqueton

Abstract

We first present briefly the CALM learning method, based upon the idea of belief. Then we state the multi‐agents scheme in which such a method can be used to predict numerical values. The basic idea is to simulate the expert's reasoning in front of a graphical display of the numerical values representing the phenomenon he wants to study: (a) First, looking at local shapes in the curve (b) Secondly, using maxima, minima and/or zero‐crossings to prevent long range errors in the prediction. We present some results on the astronomy problem presented by M. O. Menessier about the prediction of brightness variation of Mira stars.

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  • Joël Quinqueton, 1989. "Analysis of pseudo‐periodic chronological series with irregularly time‐spaced data in view to their prediction. IV. Using a symbolic learning method," Applied Stochastic Models and Data Analysis, John Wiley & Sons, vol. 5(3), pages 265-271, September.
    • Handle: RePEc:wly:apsmda:v:5:y:1989:i:3:p:265-271
    DOI: 10.1002/asm.3150050308
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