Gradient-enhanced kriging: Difference between revisions
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{{New unreviewed article|source=ArticleWizard|date=November 2016}} |
{{New unreviewed article|source=ArticleWizard|date=November 2016}} |
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'''Gradient-Enhanced Kriging (GEK)''' is a [[surrogate model|surrogate modeling]] technique used in engineering. A surrogate model (alternatively known as a [[metamodeling|metamodel]], [[response surface methodology|response surface]] or emulator) is a prediction of the output of an expensive computer code. This prediction is based on a small number of evaluations of the expensive computer code. |
'''Gradient-Enhanced Kriging (GEK)''' is a [[surrogate model|surrogate modeling]] technique used in engineering. A surrogate model (alternatively known as a [[metamodeling|metamodel]], [[response surface methodology|response surface]] or emulator) is a prediction of the output of an expensive computer code. This prediction is based on a small number of evaluations of the expensive computer code. |
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== Introduction == |
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== Kriging predictor == |
== Kriging predictor == |
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=== Kriging === |
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== GEK predictor == |
== GEK predictor == |
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Revision as of 00:32, 8 November 2016
Template:New unreviewed article Gradient-Enhanced Kriging (GEK) is a surrogate modeling technique used in engineering. A surrogate model (alternatively known as a metamodel, response surface or emulator) is a prediction of the output of an expensive computer code. This prediction is based on a small number of evaluations of the expensive computer code.