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Activity Number:
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250
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Type:
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Contributed
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Date/Time:
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Tuesday, July 31, 2007 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Physical and Engineering Sciences
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| Abstract - #309265 |
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Title:
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Blind Kriging
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Author(s):
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Roshan Vengazhiyil*+ and Ying Hung and Agus Sudjianto
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Companies:
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Georgia Institute of Technology and Georgia Institute of Technology and Bank of America
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Address:
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755 Ferst Dr NW, Atlanta, GA, 30332,
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Keywords:
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Computer experiments ; Finite element models ; Kriging ; Metamodels ; Product design ; Variable selection
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Abstract:
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Kriging is a useful method for developing metamodels for product design optimization. The most popular kriging method known as ordinary kriging uses a constant mean in the model. In this article, a modified kriging method is proposed, which has an unknown mean model. Therefore it is called blind kriging. The unknown mean model is identified from experimental data using some variable selection techniques. Many examples are presented, which show remarkable improvement in prediction using blind kriging over ordinary kriging. The blind kriging predictor is easier to interpret and also seems to be more robust to the misspecification in the correlation parameters.
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