The Gaussian Process Modeling Module in UQLab
We introduce the Gaussian process (GP) modeling module developed within the UQLab software framework. The novel design of the GP-module aims at providing seamless integration of GP modeling into any uncertainty quantification workflow, as well as a standalone surrogate modeling tool. We first briefl...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Pouyan Press
2018-07-01
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| Series: | Journal of Soft Computing in Civil Engineering |
| Subjects: | |
| Online Access: | http://www.jsoftcivil.com/article_64721_329effd7ea1841207cec9b59c663ba5c.pdf |
| _version_ | 1818416257030946816 |
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| author | Christos Lataniotis Stefano Marelli Bruno Sudret |
| author_facet | Christos Lataniotis Stefano Marelli Bruno Sudret |
| author_sort | Christos Lataniotis |
| collection | DOAJ |
| description | We introduce the Gaussian process (GP) modeling module developed within the UQLab software framework. The novel design of the GP-module aims at providing seamless integration of GP modeling into any uncertainty quantification workflow, as well as a standalone surrogate modeling tool. We first briefly present the key mathematical tools on the basis of GP modeling (a.k.a. Kriging), as well as the associated theoretical and computational framework. We then provide an extensive overview of the available features of the software and demonstrate its flexibility and user-friendliness. Finally, we showcase the usage and the performance of the software on several applications borrowed from different fields of engineering. These include a basic surrogate of a well-known analytical benchmark function; a hierarchical Kriging example applied to wind turbine aero-servo-elastic simulations and a more complex geotechnical example that requires a non-stationary, user-defined correlation function. The GP-module, like the rest of the scientific code that is shipped with UQLab, is open source (BSD license). |
| first_indexed | 2024-12-14T11:48:00Z |
| format | Article |
| id | doaj.art-91f4a495dbba473ebcc397e6d8e74761 |
| institution | Directory Open Access Journal |
| issn | 2588-2872 2588-2872 |
| language | English |
| last_indexed | 2024-12-14T11:48:00Z |
| publishDate | 2018-07-01 |
| publisher | Pouyan Press |
| record_format | Article |
| series | Journal of Soft Computing in Civil Engineering |
| spelling | doaj.art-91f4a495dbba473ebcc397e6d8e747612022-12-21T23:02:29ZengPouyan PressJournal of Soft Computing in Civil Engineering2588-28722588-28722018-07-01239111610.22115/scce.2018.129323.106264721The Gaussian Process Modeling Module in UQLabChristos Lataniotis0Stefano Marelli1Bruno Sudret2Chair of Risk, Safety and Uncertainty Quantification, ETH Zurich, Stefano-Franscini-Platz 5, 8093 Zurich, SwitzerlandETH Zurich, Stefano-Franscini-Platz 5, 8093 Zurich, SwitzerlandETH Zurich, Stefano-Franscini-Platz 5, 8093 Zurich, SwitzerlandWe introduce the Gaussian process (GP) modeling module developed within the UQLab software framework. The novel design of the GP-module aims at providing seamless integration of GP modeling into any uncertainty quantification workflow, as well as a standalone surrogate modeling tool. We first briefly present the key mathematical tools on the basis of GP modeling (a.k.a. Kriging), as well as the associated theoretical and computational framework. We then provide an extensive overview of the available features of the software and demonstrate its flexibility and user-friendliness. Finally, we showcase the usage and the performance of the software on several applications borrowed from different fields of engineering. These include a basic surrogate of a well-known analytical benchmark function; a hierarchical Kriging example applied to wind turbine aero-servo-elastic simulations and a more complex geotechnical example that requires a non-stationary, user-defined correlation function. The GP-module, like the rest of the scientific code that is shipped with UQLab, is open source (BSD license).http://www.jsoftcivil.com/article_64721_329effd7ea1841207cec9b59c663ba5c.pdfuqlabgaussian process modelingkrigingmatlabuncertainty quantification |
| spellingShingle | Christos Lataniotis Stefano Marelli Bruno Sudret The Gaussian Process Modeling Module in UQLab Journal of Soft Computing in Civil Engineering uqlab gaussian process modeling kriging matlab uncertainty quantification |
| title | The Gaussian Process Modeling Module in UQLab |
| title_full | The Gaussian Process Modeling Module in UQLab |
| title_fullStr | The Gaussian Process Modeling Module in UQLab |
| title_full_unstemmed | The Gaussian Process Modeling Module in UQLab |
| title_short | The Gaussian Process Modeling Module in UQLab |
| title_sort | gaussian process modeling module in uqlab |
| topic | uqlab gaussian process modeling kriging matlab uncertainty quantification |
| url | http://www.jsoftcivil.com/article_64721_329effd7ea1841207cec9b59c663ba5c.pdf |
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