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| Content Provider | Springer Nature Link |
|---|---|
| Author | Zhao, Dong Xue, Deyi |
| Copyright Year | 2009 |
| Abstract | Metamodeling methods have been widely used in engineering applications to create surrogate models for complex systems. In the past, the input–output relationship of the complex system is usually approximated globally using only a single metamodel. In this research, a new metamodeling method, namely multi-surrogate approximation (MSA) metamodeling method, is developed using multiple metamodels when the sample data collected from different regions of the design space are of different characteristics. In this method, sample data are first classified into clusters based on their similarities in the design space, and a local metamodel is identified for each cluster of the sample data. A global metamodel is then built using these local metamodels considering the contributions of these local metamodels in different regions of the design space. Compared with the traditional approach of global metamodeling using only a single metamodel, this MSA metamodeling method can improve the modeling accuracy considerably. Applications of this metamodeling method have also been demonstrated in this research. |
| Starting Page | 139 |
| Ending Page | 153 |
| Page Count | 15 |
| File Format | |
| ISSN | 01770667 |
| Journal | Engineering with Computers |
| Volume Number | 27 |
| Issue Number | 2 |
| e-ISSN | 14355663 |
| Language | English |
| Publisher | Springer-Verlag |
| Publisher Date | 2010-01-05 |
| Publisher Place | London |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Metamodeling Multivariate polynomial Radial basis functions Kriging Bayesian neural network Gaussian mixture model ApplicationMathematics/Computational Methods of Engineering Mechanics Math. Applications in Chemistry Computer-Aided Engineering (CAD, CAE) and Design Systems Theory, Control Calculus of Variations and Optimal Control; Optimization |
| Content Type | Text |
| Resource Type | Article |
| Subject | Engineering Computer Science Applications Modeling and Simulation Software |
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