International Journal for Numerical Methods in Engineering · 2004 · 33 citations · 18 references
EngineeringComputational EngineeringComputer ScienceComputational MechanicsFinite Element AnalysisFinite Element MethodsGraph AlgorithmsGraph TheoryMesh AnalysisMesh ProcessingNodal AnalysisStructural Finite Element AnalysisClique StructureGenetic Algorithm OptimizationGraph Theory ModelsMesh Reduction TechniquesNodal Reduction Techniques
Abstract 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.
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Neural networks: A comprehensive foundation
Ryszard Tadeusiewicz · Control Engineering Practice · 1995 · 7.3K citations