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.
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.
Multidimensional Data Visualization: Methods and Applications
252Multidimensional Data Visualization: Methods and Applications
252Product Details
ISBN-13: | 9781441902351 |
---|---|
Publisher: | Springer New York |
Publication date: | 11/09/2012 |
Series: | Springer Optimization and Its Applications , #75 |
Edition description: | 2012 |
Pages: | 252 |
Product dimensions: | 6.10(w) x 9.25(h) x 0.03(d) |