Release of the Surrogate Modeling (SUMO) Toolbox v6.1

We are proud to announce the 6.1 release of the SUrrogate MOdeling (SUMO) Toolbox.
[*] The SUMO Toolbox is a Matlab toolbox that automatically generates
a surrogate model (= a regression model, an approximation model, a metamodel) for a given data source (a simulation code, data set, Matlab function, ...) within the predefined accuracy, sample 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) are determined automatically.
For more information, screenshots, movies, downloads, etc. see: /
[*] In this release many important bugs have been fixed and new features (such as support for multi-objective model generation and Gaussian Process Models) have been added. Information about the new features and changes in this release are available here:
All users are strongly advised to upgrade (remember to delete old versions first). Upgrade instructions can be found here:
[*] We have tested everything as best we can, but if you encounter any problems when downloading or using the toolbox please let us know here:
Kind regards
The SUMO Lab Team
-- Surrogate Modeling Lab Ghent University, Belgium
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