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Theme
I-1: Uncertainty in Knowledge Interpretation and Fuzzy Data
– Dr. A. Gvishiani (Russia)
Presentation abstracts will appear here as soon as possible.
The major initial data
sets in Earth and environmental sciences are fuzzy by definition.
A similar picture can be observed in a number of other sciences;
the initial data are uncertain. Such data sets become more and
more huge; this increases the fuzziness and uncertainty of extracted
knowledge. Therefore, new mathematical methods of fuzzy logic
and artificial intelligence are becoming more and more important
in data studies and knowledge extraction and interpretation. The
session "Uncertainly in knowledge interpretation and fuzzy
data" will focus on applications of fuzzy logic to knowledge
extraction and interpretation. It will encompass environmental
and Earth science data, as well as all other types of data to
which a fuzzy logic approach is applicable. The goal of the session
is to provide a forum for theoretical and experimental researchers,
data and knowledge base developers and administrators to discuss
fuzzy logic methods and algorithms in their application to data
management and knowledge interpretation.
Submitted abstracts
include:
Comparative Mathematical
Methods of Geophysical Data Handling: Clustering and Fuzzy Clustering
A. Gvishiani, Russia, M. Diament, France, A. Galdeano, France,
S. Agajan, Russia, Sh. Bogoutdinov, Russia, A. Beriozko, Russia.
Mathematical Methods
of Artificial Intelligence in Geophysical Data Studies
J. Bonnin, France, A. Gvishiani, Russia.
New Methods to Qualify
Complex Systems Behaviour for Strategic Choices in Uncertainty
and Fuzzy Data
Albert Truyol, France
Visualization of Imperfect
Information & Data
Nahum Gershon, USA
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