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Wavefront reduction using graphs, neural networks and genetic algorithm
Author(s) -
Kaveh A.,
Bondarabady H. A. Rahimi
Publication year - 2004
Publication title -
international journal for numerical methods in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 168
eISSN - 1097-0207
pISSN - 0029-5981
DOI - 10.1002/nme.1023
Subject(s) - artificial neural network , numbering , algorithm , generalization , reduction (mathematics) , wavefront , polygon mesh , computer science , mathematics , mathematical optimization , artificial intelligence , geometry , mathematical analysis , physics , optics
This paper presents an algorithm for nodal numbering in order to obtain a small wavefront. Element clique graphs are employed as the mathematical models of finite element meshes. A priority function containing five vectors is used, which can be viewed as a generalization of Sloan's function. These vectors represent different connectivity properties of the graph models. Unlike Sloan's algorithm, which uses two fixed coefficients, here, five coefficients are employed, based on an evaluation by artificial neural networks. The networks weights are obtained using a simple genetic algorithm. Examples are included to illustrate the performance of the present hybrid method. Copyright © 2004 John Wiley & Sons, Ltd.