This book highlights recent developments in multidimensional
data visualization, presenting both new methods and modifications
on classic techniques. Throughout the book, various applications of
multidimensional data visualization are presented including its
uses in social sciences (economy, education, politics, psychology),
environmetrics, and medicine (ophthalmology, sport medicine,
pharmacology, sleep medicine).
The book provides recent research results in optimization-based
visualization. Evolutionary algorithms and a two-level optimization
method, based on combinatorial optimization and quadratic
programming, are analyzed in detail. The performance of these
algorithms and the development of parallel versions is
discussed.
The encorporation of new visualization techniques to improve the
capabilies of artificial neural networks (self-organizing maps,
feed-forward networks) is also discussed.
The book includes over 100 detailed images presenting examples
of the different visualization techniques that are presented.
This book is intended for scientists and researchers in any
field of study where complex and multidimensional data must be
represented visually.
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