DDS: Difference between revisions

From BlueM
Jump to navigation Jump to search
(Die Seite wurde neu angelegt: {{EVO.NET nav}} ==Beschreibung== '''Dynamically Dimensioned Search''' (DDS) is an n-dimensional continuous global optimization algorithm by {{:Literatur:Tolson-Shoemak...)
 
m (Umbenennung EVO.NET -> BlueM.Opt)
Line 1: Line 1:
{{EVO.NET nav}}
{{BlueM.Opt nav}}


==Beschreibung==
==Beschreibung==
Line 17: Line 17:
<references/>
<references/>


[[Kategorie:EVO]]
[[Kategorie:BlueM.Opt Anwendung]]

Revision as of 03:47, 26 March 2009

EVO.png BlueM.Opt | Download | Usage | Development

Beschreibung

Dynamically Dimensioned Search (DDS) is an n-dimensional continuous global optimization algorithm by Tolson & Shoemaker (2007)[1].

DDS is designed for calibration problems with many parameters, requires no algorithm parameter tuning, and automatically scales the search to find good solutions within the maximum number of user-specified function (or model) evaluations. As a result, DDS is ideally suited for computationally expensive optimization problems such as distributed watershed model calibration.[1]

Erforderliche Eingabedateien

Literaturangaben

  1. ↑ 1.0 1.1 Tolson, B. A., and C. A. Shoemaker (2007): Dynamically dimensioned search algorithm for computationally efficient watershed model calibration, Water Resources Research 43, W01413, doi:10.1029/2005WR004723.
Retrieved from "https://wiki.bluemodel.org/index.php?title=DDS&oldid=6075"