Multidimensional Data Visualization

Methods and Applications

Nonfiction, Science & Nature, Mathematics, Applied, Computers
Cover of the book Multidimensional Data Visualization by Gintautas Dzemyda, Olga Kurasova, Julius Žilinskas, Springer New York
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Author: Gintautas Dzemyda, Olga Kurasova, Julius Žilinskas ISBN: 9781441902368
Publisher: Springer New York Publication: November 8, 2012
Imprint: Springer Language: English
Author: Gintautas Dzemyda, Olga Kurasova, Julius Žilinskas
ISBN: 9781441902368
Publisher: Springer New York
Publication: November 8, 2012
Imprint: Springer
Language: English

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 are discussed.

The utilization 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 many different visualization techniques that the book presents.

This book is intended for scientists and researchers in any field of study where complex and multidimensional data must be represented visually.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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 are discussed.

The utilization 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 many different visualization techniques that the book presents.

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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