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Multidimensional Data Visualization: Methods and Applications: 75 (Springer Optimization and Its Applications, 75) - Tapa dura

Libro 67 de 176: Springer Optimization and Its Applications

Dzemyda, Gintautas; Žilinskas, Julius; Kurasova, Olga

 
9781441902351: Multidimensional Data Visualization: Methods and Applications: 75 (Springer Optimization and Its Applications, 75)
Tapa dura
ISBN 10: 144190235X ISBN 13: 9781441902351
Editorial: Springer, 2012

Sinopsis

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.

"Sinopsis" puede pertenecer a otra edición de este libro.

De la contraportada

The goal of this book is to present a variety of methods used in multidimensional data visualization. The emphasis is placed on new research results and trends in this field, including optimization, artificial neural networks, combinations of algorithms, parallel computing, different proximity measures, nonlinear manifold learning, and more. Many of the applications presented allow us to discover the obvious advantages of visual data mining it is much easier for a decision maker to detect or extract useful information from graphical representation of data than from raw numbers.

The fundamental idea of visualization is to provide data in some visual form that lets humans understand them, gain insight into the data, draw conclusions, and directly influence the process of decision making. Visual data mining is a field where human participation is integrated in the data analysis process; it covers data visualization and graphical presentation of information.

Multidimensional Data Visualization is intended for scientists and researchers in any field of study where complex and multidimensional data must be visually represented. It may also serve as a useful research supplement for PhD students in operations research, computer science, various fields of engineering, as well as natural and social sciences.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2012
Idioma
Inglés
ISBN 10 
144190235X
ISBN 13 
9781441902351
Encuadernación
Tapa dura
Número de páginas
264
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