Interval-Related Talks at the
North American Fuzzy Information Processing
Society Annual Conference NAFIPS’06
Montreal, Quebec, Canada, June 3–6, 2006
On June 3–6, 2006, the annual conference of the North American Fuzzy Infor-
mation Processing Society (NAFIPS) was held in Montreal, Quebec, Canada. The
main objective of this conference was to bring together researchers, engineers
and practitioners to present the latest achievements and innovations in the area
of fuzzy information processing, to discuss thought-provoking developments and
challenges, and to consider potential future directions.
The relation between fuzzy and interval techniques is well known in fuzzy
community; e.g., due to the fact that a fuzzy number can be represented as a nested
family of intervals (alpha-cuts), level-by-level interval techniques are often used to
process fuzzy data.
At present, researchers in fuzzy data processing mainly used interval techniques
originally designed for non-fuzzy applications, techniques which are often taken
from textbooks and are, therefore, already outperformed by more recent and more
efﬁcient methods. It is therefore desirable to make the fuzzy community at-large
better acquainted with the latest, most efﬁcient interval techniques, especially with
techniques speciﬁcally developed for solving fuzzy-related problems. For this pur-
pose, a special session on inter-relation between interval and fuzzy techniques was
organized at NAFIPS’06.
Another objective of this session was to combine fuzzy and interval techniques,
so that we will be able to use the combined techniques in (frequent) practical situa-
tions where both types of uncertainty are present: for example, when some quantities
are known with interval uncertainty (e.g., coming from measurements), while other
quantities are known with fuzzy uncertainty (coming from expert estimates).
Due to the close relation between interval and fuzzy techniques, interval methods
were mentioned not only in the papers from the interval session, but also in several
other talks presented at the conference. In particular, the need for adding interval
uncertainty to fuzzy techniques was one of the main points of a plenary talk of
urks¸enonFoundational Concerns in Fuzzy Theory.
Several talks described how level-by-level interval computations can be used to
process fuzzy data. For example, M. Ning, M. Zaheeruddin, and Z. Chen applied
Reliable Computing (2007)