How can we solve engineering problems while taking into account data
characterized by different types of measurement and estimation
uncertainty: interval, probabilistic, fuzzy, etc.? This book provides a
theoretical basis for arriving at such solutions, as well as case
studies demonstrating how these theoretical ideas can be translated into
practical applications in the geosciences, pavement engineering, etc.
In all these developments, the authors' objectives were to provide
accurate estimates of the resulting uncertainty; to offer solutions that
require reasonably short computation times; to offer content that is
accessible for engineers; and to be sufficiently general - so that
readers can use the book for many different problems. The authors also
describe how to make decisions under different types of uncertainty.
The book offers a valuable resource for all practical engineers
interested in better ways of gauging uncertainty, for students eager to
learn and apply the new techniques, and for researchers interested in
processing heterogeneous uncertainty.