Paper Info
Title
A Hybrid Algorithm Based on Evolution Strategies and Instance-Based Learning, Used in Two-Dimensional Fitting of Brightness Profiles in Galaxy Images
Abstract
The hybridization of optimization techniques can exploit the strengths of different approaches and avoid their weaknesses. In this work we present a hybrid optimization algorithm based on the combination of Evolution Strategies (ES) and Locally Weighted Linear Regression (LWLR). In this hybrid a local algorithm (LWLR) proposes a new solution that is used by a global algorithm (ES) to produce new better solutions. This new hybrid is applied in solving an interesting and difficult problem in astronomy, the two-dimensional fitting of brightness profiles in galaxy images.The use of standardized fitting functions is arguably the most powerful method for measuring the large-scale features (e.g. brightness distribution) and structure of galaxies, specifying parameters that can provide insight into the formation and evolution of galaxies. Here we employ the hybrid algorithm ES+LWLR to find models that describe the bi-dimensional brightness profiles for a set of optical galactic images. Models are created using two functions: de Vaucoleurs and exponential, which produce models that are expressed as sets of concentric generalized ellipses that represent the brightness profiles of the images.The problem can be seen as an optimization problem because we need to minimize the difference between the flux from the model and the flux from the original optical image, following a normalized Euclidean distance. We solved this optimization problem using our hybrid algorithm ES+LWLR. We have obtained results for a set of 100 galaxies, showing that hybrid algorithm is very well suited to solve this problem.
Year
DOI
Venue
2007
10.1007/978-3-540-73499-4_54
MLDM
Keywords
Field
DocType
bi-dimensional brightness profile,hybrid optimization algorithm,global algorithm,brightness profile,local algorithm,new hybrid,galaxy images,evolution strategies,hybrid algorithm,difficult problem,brightness profiles,optimization problem,brightness distribution,instance-based learning,euclidean distance,linear regression,optical imaging,evolution strategy,fitness function,instance based learning,power method
Hybrid algorithm,Instance-based learning,Pattern recognition,Computer science,Euclidean distance,Local algorithm,Surface brightness,Artificial intelligence,Optimization problem,Brightness,Machine learning,Difference-map algorithm
Conference
Volume
ISSN
Citations 
4571
0302-9743
0
PageRank 
References 
Authors
0.34
5
2
Name
Order
Citations
PageRank
Juan Carlos Gomez18412.89
Olac Fuentes224634.55