© 2014 © 2014 Taylor & Francis. The accuracy of metamodelling is determined by both the sampling and approximation. This article proposes a new sampling method based on the zeros of Chebyshev polynomials to capture the sampling information effectively. First, the zeros of one-dimensional Chebyshev polynomials are applied to construct Chebyshev tensor product (CTP) sampling, and the CTP is then used to construct high-order multi-dimensional metamodels using the hypercube polynomials. Secondly, the CTP sampling is further enhanced to develop Chebyshev collocation method (CCM) sampling, to construct the simplex polynomials. The samples of CCM are randomly and directly chosen from the CTP samples. Two widely studied sampling methods, namely the...
A major challenge of metamodeling in simulation-based engineering design optimization is to handle t...
AbstractThis paper deals with the problem of the polynomial interpolation of data subject to bounded...
This paper proposes a new deterministic sampling strategy for constructing polynomial chaos approxim...
Purpose - The sampling methods (or design of experiments) which have large influence on the performa...
which permits unrestricted use, distribution, and reproduction in any medium, provided the original ...
In the paper, the method of weighted polynomials for model building on the basis of numerical or phy...
The widespread use of computer experiments for design optimization has made the issue of reducing co...
Metamodels approximate complex multivariate data sets from simulations and experiments. These data s...
© 2015. This study will develop a new high-order polynomial surrogate model (HOPSM) to overcome rout...
High Dimensional Model Representation (HDMR) offers efficient ways to approximate computation-intens...
This paper introduces a technique for reducing the sampling size necessary to explore a design space...
Abstract. Metamodelling decreases the computational effort of time-consuming computer simulations by...
Abstract Metamodels are widely used during the design process in place of expensive simulation model...
Metamodeling is becoming a rather popular means to approximate the expensive simulations in today’s ...
There is a continuing interplay between mathematics and survey methodology involving different branc...
A major challenge of metamodeling in simulation-based engineering design optimization is to handle t...
AbstractThis paper deals with the problem of the polynomial interpolation of data subject to bounded...
This paper proposes a new deterministic sampling strategy for constructing polynomial chaos approxim...
Purpose - The sampling methods (or design of experiments) which have large influence on the performa...
which permits unrestricted use, distribution, and reproduction in any medium, provided the original ...
In the paper, the method of weighted polynomials for model building on the basis of numerical or phy...
The widespread use of computer experiments for design optimization has made the issue of reducing co...
Metamodels approximate complex multivariate data sets from simulations and experiments. These data s...
© 2015. This study will develop a new high-order polynomial surrogate model (HOPSM) to overcome rout...
High Dimensional Model Representation (HDMR) offers efficient ways to approximate computation-intens...
This paper introduces a technique for reducing the sampling size necessary to explore a design space...
Abstract. Metamodelling decreases the computational effort of time-consuming computer simulations by...
Abstract Metamodels are widely used during the design process in place of expensive simulation model...
Metamodeling is becoming a rather popular means to approximate the expensive simulations in today’s ...
There is a continuing interplay between mathematics and survey methodology involving different branc...
A major challenge of metamodeling in simulation-based engineering design optimization is to handle t...
AbstractThis paper deals with the problem of the polynomial interpolation of data subject to bounded...
This paper proposes a new deterministic sampling strategy for constructing polynomial chaos approxim...