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Springer Optimization and Its Applications Ser.: Multidimensional Data Visualization : Methods and Applications by Julius Žilinskas, Olga Kurasova and Gintautas Dzemyda (2012, Hardcover)
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About this product
Product Identifiers
PublisherSpringer New York
ISBN-10144190235X
ISBN-139781441902351
eBay Product ID (ePID)14038835566
Product Key Features
Number of PagesXii, 252 Pages
LanguageEnglish
Publication NameMultidimensional Data Visualization : Methods and Applications
Publication Year2012
SubjectComputer Simulation, Graphic Methods, Library & Information Science / General, Optimization
TypeTextbook
AuthorJulius Žilinskas, Olga Kurasova, Gintautas Dzemyda
Subject AreaMathematics, Computers, Language Arts & Disciplines
SeriesSpringer Optimization and Its Applications Ser.
FormatHardcover
Dimensions
Item Weight183.7 Oz
Item Length9.3 in
Item Width6.1 in
Additional Product Features
Intended AudienceScholarly & Professional
LCCN2012-946732
Dewey Edition23
Series Volume Number75
Number of Volumes1 vol.
IllustratedYes
Dewey Decimal006.6
Table Of ContentPreface.- 1. Multidimensional Data and the Concept of Visualization.- 2. Strategies for Multidimensional Data Visualization.- 3. Optimization-Based Visualization.- 4. Combining Multidimensional Scaling with Artificial Neural Networks.- 5. Applications of Visualizations.- A. Test Data Sets.- References.- Index.
SynopsisThis 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., This book presents a variety of methods used in multidimensional data visualization. It details new research results and trends in the field, including optimization, artificial neural networks, combinations of algorithms, and parallel computing., 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.
LC Classification NumberQA402.5-402.6
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