Re: Fuzzy and Neural

[EMAIL PROTECTED] (Bruno) wrote in message news:<[EMAIL PROTECTED]>...
> Somebody has a paper about the Fuzzy advantages´s over Neural Network?
> 
> Best Regards!
> 
> Allan Bruno

Hello 

Appended is an excerp from an articl found in web.
The whole article is to be found in:
www.fuzzytech.com … seminars + workshop … 
Introduction to NeuroFuzzy Technologies

best regards 
Robert Bohlen

Combining Neural and Fuzzy
The key benefit of fuzzy logic is, that it lets you describe desired
system behavior with simple "if-then" relations. In many applications,
this gets you a simpler solution in less design time. In addition, you
can use all available engineering know-how to optimize the performance
directly.
While this is certainly the beauty of fuzzy logic, it at the same time
is its major limitation. In many applications, knowledge that
describes desired system behavior is contained in data sets. Here, the
designer has to derive the "if-then" rules from the data sets
manually, which requires a major effort with large data sets.
When data sets contain knowledge about the system to be designed, a
neural net promises a solution as it can train itself from the data
sets. However, only few commercial applications of neural nets exist.
This is a contrast to fuzzy logic, which is a very common design
technique in Asia and Europe.
The sparse use of neural nets in applications is due to a number of
reasons. First, neural net solutions remain a "black box". You can
neither interpret what causes a certain behavior nor can you modify a
neural net manually to change a certain behavior. Second, neural nets
require prohibitive computational effort for most mass-market
products. Third, selection of the appropriate net model and setting
the parameters of the learning algorithm is still a "black art" and
requires long experience. Of the aforementioned reasons, the lack of
an easy way to verify and optimize a neural net solution is probably
the mayor limitation.
In simple words, both neural nets and fuzzy logic are powerful design
techniques that have its strengths and weaknesses. Neural nets can
learn from data sets while fuzzy logic solutions are easy to verify
and optimize. If you look at these properties in a portfolio, the idea
becomes obvious, that a clever combination of the two technologies
delivers best of both worlds. Combine the explicit knowledge
representation of fuzzy logic with the learning power of neural nets,
and you get NeuroFuzzy.