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This book addresses the basics of interval/fuzzy set theory,
artificial neural networks (ANN) and computational methods. It
presents step-by-step modeling for application problems along with
simulation and numerical solutions. In general, every science and
engineering problem is inherently biased by uncertainty, and there
is often a need to model, solve and interpret problems in the world
of uncertainty. At the same time, exact information about models
and parameters of practical applications is usually not known and
precise values do not exist. This book discusses uncertainty in
both data and models. It consists of seven chapters covering
various aspects of fuzzy uncertainty in application problems, such
as shallow water wave equations, static structural problems,
robotics, radon diffusion in soil, risk of invasive alien species
and air quality quantification. These problems are handled by means
of advanced computational and fuzzy theory along with machine
intelligence when the uncertainties involved are fuzzy. The
proposed computational methods offer new fuzzy computing methods
that help other areas of knowledge construction where inexact
information is present.
This book addresses the basics of interval/fuzzy set theory,
artificial neural networks (ANN) and computational methods. It
presents step-by-step modeling for application problems along with
simulation and numerical solutions. In general, every science and
engineering problem is inherently biased by uncertainty, and there
is often a need to model, solve and interpret problems in the world
of uncertainty. At the same time, exact information about models
and parameters of practical applications is usually not known and
precise values do not exist. This book discusses uncertainty in
both data and models. It consists of seven chapters covering
various aspects of fuzzy uncertainty in application problems, such
as shallow water wave equations, static structural problems,
robotics, radon diffusion in soil, risk of invasive alien species
and air quality quantification. These problems are handled by means
of advanced computational and fuzzy theory along with machine
intelligence when the uncertainties involved are fuzzy. The
proposed computational methods offer new fuzzy computing methods
that help other areas of knowledge construction where inexact
information is present.
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