نتایج جستجو برای: rbfs
تعداد نتایج: 430 فیلتر نتایج به سال:
The meshless local Petrov–Galerkin (MLPG) method with radial basis functions (RBFs), and the higher order shear and normal deformable plate theory (HOSNDPT) are used to analyze static infinitesimal deformations of thick laminated composite elastic plates under different boundary conditions. Two types of RBFs, namely, multiquadrics (MQ) and thin plate splines (TPS), are employed for constructing...
A-priori individual interconnect length estimates can be used to make placement efficient and reduce delay and power consumption in a circuit. However, finding lengths of individual interconnects before their terminals have been placed can be a daunting task. In this thesis, the main characteristics that need to be considered while designing an individual a-priori length estimation technique fo...
A new projection method based on radial basis functions (RBFs) is presented for discretizing the incompressible unsteady Stokes equations in irregular geometries. The novelty of the method comes from the application of a new technique for computing the Leray-Helmholtz projection of a vector field using generalized interpolation with divergence-free and curl-free RBFs. Unlike traditional project...
Abstract. Radial basis functions (RBFs) are a powerful tool for interpolating/approximating multidimensional scattered data. Notwithstanding, RBFs pose computational challenges, such as the efficient evaluation of an n-center RBF expansion at m points. A direct summation requires O(nm) operations. We present a new multilevel method whose cost is only O((n + m) ln(1/δ)), where δ is the desired a...
In this paper, an improved meshfree scheme based on radial basis functions (RBFs) is provided for solving the incompressible viscous Navier–Stokes equations and two enhancements are proposed to mitigate typical numerical oscillations. The first one combination of RBFs-based finite difference (RBF-FD) method with semi-Lagrangian RBFs (SLM-RBF), former being used diffusion term pressure Poisson e...
Abstract. We construct a new adaptive algorithm for radial basis functions (RBFs) method applied to interpolation, boundary-value, and initialboundary-value problems with localized features. Nodes can be added and removed based on residuals evaluated at a finer point set. We also adapt the shape parameters of RBFs based on the node spacings to prevent the growth of the conditioning of the inter...
A framework with a combination of the radial basis functions (RBFs) method and the least-squares integration method is proposed to improve the integration process from gradient to shape. The principle of the framework is described, and the performance of the proposed method is investigated by simulation. Improvement in accuracy is verified by comparing the result with the usual RBFs-based subse...
CMACs and Radial Basis Functions are often used in reinforcement learning to learn value function approximations having local generalization properties. We examine the similarities and differences between CMACs, RBFs and normalized RBFs and compare the performance of Q-learning with each representation applied to the mountain car problem. We discuss ongoing research efforts to exploit the flexi...
Very few studies involve how to construct the efficient RBFs by means of problem features. Recently the present author presented general solution RBF (GS-RBF) methodology to create operator-dependent RBFs successfully [1]. On the other hand, the normal radial basis function (RBF) is defined via Euclidean space distance function or the geodesic distance [2]. This purpose of this note is to redef...
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