WSEAS Transactions on Computers
Print ISSN: 1109-2750, E-ISSN: 2224-2872
Volume 14, 2017
Mesh Refinement with Finite Elements and Artificial Neural Networks
Authors: ,
Abstract: In this paper, we present a new modeling for Mesh-size refinement with finite elements and artificial neural networks adopted by standards actual videos based on the SOM for image one domain, in the form of a structure. We developed in this study a mesh based on the object of interest by finite elements method and reduce the effort required to apply finite element analysis to image, this presentation that allows the identification of edges is a good representation of the movement of network nodes, and then we approach the follow-up of objects on sequences of Mesh-size refinement images. The algorithm of SOM the Kohonen is one of the important methods; it is a biologically inspired data clustering technique. It is a question of determining the Mesh adapte of an object nets, from one image to another. For that we used the algorithm allowing following a deformable plane object. On the one hand, we improve its performance, and then we study the optimization of the error function by error the Mesh-size refinement object simplification of our model, among the different meshes associated with images references. At the end of this work, we present simulation results.
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Keywords: Refinement mesh-size, Learning Kohonen SOM, Mesh-size by Finite Elements, deformation the Mesh-size refinement, interpolation
Pages: 335-344
WSEAS Transactions on Computers, ISSN / E-ISSN: 1109-2750 / 2224-2872, Volume 14, 2017, Art. #39