A Sequential Optimization Sampling Method for Metamodels with Radial Basis Functions

A Sequential Optimization Sampling Method for Metamodels with Radial Basis Functions

Metamodels have been widely used in engineering design to facilitate analysis and optimization of complex systems that involve computationally expensive simulation programs. The accuracy of metamodels is strongly affected by the sampling methods. In this paper, a new sequential optimization sampling method is proposed. Based on the new sampling method, metamodels can be constructed repeatedly t...

The method of radial basis functions for the solution of nonlinear Fredholm integral equations system.

In this paper, An effective and simple numerical method is proposed for solving systems of integral equations using radial basis functions (RBFs). We present an algorithm based on interpolation by radial basis functions including multiquadratics (MQs), using Legendre-Gauss-Lobatto nodes and weights. Also a theorem is proved for convergence of the algorithm. Some numerical examples are presented...

MQ-Radial Basis Functions Center Nodes Selection with PROMETHEE Technique

In this paper‎, ‎we decide to select the best center nodes‎ ‎of radial basis functions by applying the Multiple Criteria Decision‎ ‎Making (MCDM) techniques‎. ‎Two methods based on radial basis‎ ‎functions to approximate the solution of partial differential‎ ‎equation by using collocation method are applied‎. ‎The first is based‎ ‎on the Kansa's approach‎, ‎and the second is based on the Hermit...

A radial basis functions method for fractional diffusion equations

Article history: Received 13 April 2012 Received in revised form 10 October 2012 Accepted 27 October 2012 Available online 8 December 2012

A Quasi-radial Basis Functions Method for American Options Pricing