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We are happy to announce the 6.2.1 release of the SUrrogate MOdeling
(SUMO) Toolbox.
[*] The SUMO Toolbox is a Matlab toolbox that automatically generates
a metamodel (= a regression model, a response surface model) for a
given data source (a simulation code, data set, Matlab function, ...)
within the predefined accuracy, simulation budget, and time limits set
by the user.
[*] It will automatically drive your simulation code generating an
approximation model (ANN, SVM, rational function, RBF model, spline,
Kriging, ...) that is as accurate as possible, using as little data
points as possible (since these are usually expensive). Sample
selection is done adaptively (= active learning, adaptive sampling)
and the model parameters (e.g., ANN topology, SVM parameters,...) are
determined automatically.
For more information, screenshots, movies, downloads, etc. see:
http://www.sumowiki.intec.ugent.be/
[*] In this release many important bugs have been fixed and new
features have been added. This includes better (blind) kriging
models, more flexible adaptive sampling methods, and an improved model
browser. Details can be found here:
http://www.sumowiki.intec.ugent.be/index.php/Whats_new
http://www.sumowiki.intec.ugent.be/index.php/Changelog
[*] Any questions, or feedback is greatly appreciated, you can let us
know here:
http://www.sumowiki.intec.ugent.be/index.php/Contact
Kind regards
The SUMO Lab Team
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Surrogate Modeling Lab
Ghent University, Belgium
web: http://www.sumo.intec.ugent.be
blog: http://sumolab.blogspot.com/
youtube: http://www.youtube.com/sumolab |
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