A Novel Combination Co-Kriging Model Based on Gaussian Random Process
Joint Authors
Xie, Huan
Zeng, Wei
Song, Hong
Sun, Wen
Ren, Tao
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-09-03
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Co-Kriging (CK) modeling provides an efficient way to predict responses of complicated engineering problems based on a set of sample data obtained by methods with varying degree of accuracy and computation cost.
In this work, the Gaussian random process (GRP) is introduced to construct a novel combination CK model (CK-GRP) to improve the prediction accuracy of the conventional CK model, in which all the sample information provided by different correlation models is well utilized.
The features of the new model are demonstrated and evaluated for a numerical case and an engineering application.
It is shown that the CK-GRP model proposed in this work is effective and can be used to improve the prediction accuracy and robustness of the CK model.
American Psychological Association (APA)
Xie, Huan& Zeng, Wei& Song, Hong& Sun, Wen& Ren, Tao. 2018. A Novel Combination Co-Kriging Model Based on Gaussian Random Process. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1208353
Modern Language Association (MLA)
Xie, Huan…[et al.]. A Novel Combination Co-Kriging Model Based on Gaussian Random Process. Mathematical Problems in Engineering No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1208353
American Medical Association (AMA)
Xie, Huan& Zeng, Wei& Song, Hong& Sun, Wen& Ren, Tao. A Novel Combination Co-Kriging Model Based on Gaussian Random Process. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1208353
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1208353