Re: coupling neural networks and fuzzy logic for forecasting purposes

From: Giorgio Corani (corani@elet.polimi.it)
Date: Wed Nov 28 2001 - 11:17:15 MET

  • Next message: Tomas Jura: "Re: coupling neural networks and fuzzy logic for forecasting purposes"

    Harris Georgiou wrote:

    > "Giorgio Corani" <corani@elet.polimi.it> wrote in message
    > news:3C0360CD.10004@elet.polimi.it...
    >
    >>...........
    >>Roughly speaking: an identical rainfall event causes a small water
    >>level increase if the soil is dry, and a very larger increase is the
    >>soil is wet and does not infiltrate water.
    >>
    >>The problem i would to address is that my knowledge about the state of
    >>the system is quite fuzzy (i can say for example the basin is more or
    >>less wet)...................
    >>
    >
    > Why not use the dryness of the soil as an independent input itself? Even if
    > the estimation is subjective, you can use a scale from 1 to 10 (or whatever)
    > and include this estimation in the input vector. If that estimation is
    > fairly good, the training process will determine if and how much it affects
    > the output of the system. Just a thought.

    I already thought about that. In my opinion it could not be really
    useful: although it is possible to select a "class of dryness" for the
    state of the soil, it will represents actually the state of the system,
    not an input to it.
    Since identical rainfall (i.e. identical inputs) results in a very
    different runoff (i.e. different outputs) depending on the dryness of
    the soil, the dryness of the soil has in fact the role of a state variable.
    I think that such state variable could not be very useful is used as
    input to the system.

    > If you are interested in combining NN with fuzzy rules, take a look at:
    > "Neuro-Fuzzy and Soft computing"
    > J-S R Jang, C-T Sun, E Mizutani
    > Prentice-Hall, 1997

    I thank you for your suggestion, I will search for that book.

    > Harris
    >

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