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.