DATA-BEST 2018

DATA-BEST 2018

SECOND INTERNATIONAL WORKSHOP ON DATABASED ENGINEERING, SCIENCE AND TECHNOLOGY NOVEMBER 13-15, 2018

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SECOND INTERNATIONAL WORKSHOP ON DATABASED ENGINEERING, SCIENCE AND TECHNOLOGY NOVEMBER 13-15, 2018


Engineering sciences and technology, as any other branch of sciences and technology, is experiencing the data revolution. In the past models were more
abundant than data, too expensive to be collected and analyzed at that time. However, nowadays, the situation is radically different, data is much more abundant (and accurate) than existing models, and a new paradigm is
emerging in engineering sciences and technology. Advanced clustering techniques not only helps engineers and analysts, they become crucial in many
areas where models, approximation bases, parameters, … are adapted depending on the local (in space and
time senses) state of the system.
Machine learning is also helping for extracting the
manifold in which the solutions of complex and
coupled engineering problems are living. Thus,
uncorrelated parameters can be efficiently extracted
from the collected data coming from numerical
simulations, experiments or even from the data
collected from adequate measurement devices. As soon
as uncorrelated parameters are identified (constituting
the information level), the solution of the problem can
be predicted in new points of the parametric space,
from adequate interpolations (e.g. the nearest point on
the manifold defined from the admissible solutions) or
even more, parametric solutions can be obtained within
an adequate framework able to circumvent the curse of
dimensionality (combinatorial explosion) for any value
of the uncorrelated model parameters.
Thus, the subtle circle is closed by linking data to
information, information to knowledge and finally
knowledge to real time decision-making, opening
unimaginable possibilities within the so-called DDDAS (Dynamic Data Driven Application Systems).