However, if A and B were strongly negatively associated, max-min wouldn't work
well. In this situation bounded sum ans difference would work well, with a AND
b = max(0, 1 - (a + b)) and a OR b = min(1, a+b).
But this kind of reasoning is only appropriate if we have PRIOR associations.
In the case of two sensors measuring pretty much the same thing on a process,
we would have reasonably reliable prior associations. We're up against the same
thing that plagues Bayes' theorem - what are the priors? Mostly we don't know,
and max-min is a good default.
William Siler
############################################################################
This message was posted through the fuzzy mailing list.
(1) To subscribe to this mailing list, send a message body of
"SUB FUZZY-MAIL myFirstName mySurname" to listproc@dbai.tuwien.ac.at
(2) To unsubscribe from this mailing list, send a message body of
"UNSUB FUZZY-MAIL" or "UNSUB FUZZY-MAIL yoursubscription@email.address.com"
to listproc@dbai.tuwien.ac.at
(3) To reach the human who maintains the list, send mail to
fuzzy-owner@dbai.tuwien.ac.at
(4) WWW access and other information on Fuzzy Sets and Logic see
http://www.dbai.tuwien.ac.at/ftp/mlowner/fuzzy-mail.info
(5) WWW archive: http://www.dbai.tuwien.ac.at/marchives/fuzzy-mail/index.html