I read with attention you response about this subject....
I'm agree with you considerations on argument, but I think that the
imprecision is the natural aspect of fuzzy logic .
I think that the uncertainty is linked whit probability concept.
If I say that an object ( eg. apple) is 0.75( or 75%) an apple I expose a
uncertainty but if I say this obj belongs 0.8 to apple membership, I
means an imprecision.
So in the probability topic I say that this obj is or isn't an apple ( with
grade of probability( in ex: 75%)) ( uncertainty), in the Fuzzy topic I say
that this obj is a "wrong apple" but is an apple( imprecision).
I hope that I explained my concept in the better manner.....
I love to say that probability is a distance measure from true and the fuzzy
is a distance measure from real.
Where my reasoning is wrong?
What do you think about it?
Rich Shepard <firstname.lastname@example.org> wrote in message
> On Tue, 01 May 2001 08:43:43 GMT, Cristian Fabbi <email@example.com>
> >Soon I've read that neural system made with FL think like humans (i'm
> >Why do we say so? Have we got proofs that human brain works in a fuzzy
> Your confusion comes from the well-known problem associated with the
> "fuzzy". When applied to fuzzy sets, fuzzy logic and fuzzy system models
> term means "uncertainty". Let me back up and explain.
> When we measure something in the natural world (human or non-human),
> are two sources of potential error: imprecision and uncertainty.
> comes from our inability to measure something with absolute accuracy, for
> example, the temperature of soils or the intelligence of humans. On the
> other hand, we encounter uncertainty -- or fuzziness -- when describing
> temperatures or human intelligence.
> Consider what we mean by "warm", "cool", "smart" and "dumb". These terms
> describe a relative condition that is a function of what we are measuring,
> and they can mean different things to different people or under different
> circumstances. It is this latter situation -- uncertainty in the meaning
> descriptive terms -- that we quantify in fuzzy sets, manipulate using
> logic and apply to real-world problems with fuzzy system models.
> As Lotfi Zadeh explained, the term "fuzzy" is not the best to use, but
> chosen for what seemed, at that time, to be a good reason. Think of it as
> the inherent "sloppyness" of a system, not of our measurements of the
> For your original question, the answer is "yes", humans think in fuzzy
> terms. We talk of "steep" slopes, "high speed" railroad systems, "tall"
> "short" people. These are imprecise terms that describe characteristics of
> the system we're considering.
> Dr. Richard B. Shepard, President
> Applied Ecosystem Services, Inc. (TM)
> 2404 SW 22nd Street | Troutdale, OR 97060-1247 | U.S.A.
> + 1 503-667-4517 (voice) | + 1 503-667-8863 (fax) |
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