A local meshless method based on moving least squares and local radial basis functions

2015 ◽  
Vol 50 ◽  
pp. 395-401 ◽  
Author(s):  
Baiyu Wang
Keyword(s):  
Least Squares ◽  
Radial Basis Functions ◽  
Meshless Method ◽  
Basis Functions ◽  
Moving Least Squares ◽  
Radial Basis

scholarly journals Enhancing SPH using Moving Least-Squares and Radial Basis Functions

2006 ◽  
pp. 103-112
Author(s):  
Robert Brownlee ◽  
Paul Houston ◽  
Jeremy Levesley ◽  
Stephan Rosswog
Keyword(s):  
Least Squares ◽  
Radial Basis Functions ◽  
Basis Functions ◽  
Moving Least Squares ◽  
Radial Basis

Solution for fractional distributed optimal control problem by hybrid meshless method

2016 ◽  
Vol 24 (11) ◽  
pp. 2149-2164 ◽  
Author(s):  
Majid Darehmiraki ◽  
Mohammad Hadi Farahi ◽  
Sohrab Effati
Keyword(s):  
Optimal Control ◽  
Partial Differential Equations ◽  
Differential Equations ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Least Squares ◽  
Meshless Method ◽  
Basis Functions ◽  
Moving Least Squares ◽  
Distributed Optimal Control

We use a hybrid local meshless method to solve the distributed optimal control problem of a system governed by parabolic partial differential equations with Caputo fractional time derivatives of order α ∈ (0, 1]. The presented meshless method is based on the linear combination of moving least squares and radial basis functions in the same compact support, this method will change between interpolation and approximation. The aim of this paper is to solve the system of coupled fractional partial differential equations, with necessary and sufficient conditions, for fractional distributed optimal control problems using a combination of moving least squares and radial basis functions. To keep matters simple, the problem has been considered in the one-dimensional case, however the techniques can be employed for both the two- and three-dimensional cases. Several test problems are employed and results of numerical experiments are presented. The obtained results confirm the acceptable accuracy of the proposed method.

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