Large Scale Simulations of a Neural Network Model for the Graph Bisection Problem on Geometrically Connected Graphs. Salinas, L. C. & Hernández, G. Electronic Notes in Discrete Mathematics, 18:151-156, 2004. doi abstract bibtex In this work some preliminary numerical results obtained by large scale simulations of the sequential dynamics of a neural network model for the graph bisection problem on random geometrically connected graphs are presented. It can be concluded that the sequential dynamic is a low cost, effective and very fast local minima optimization heuristic for the Graph Bisection Problem. © 2005 Elsevier B.V. All rights reserved.
@article{10.1016/j.endm.2004.06.024,
abstract = "In this work some preliminary numerical results obtained by large scale simulations of the sequential dynamics of a neural network model for the graph bisection problem on random geometrically connected graphs are presented. It can be concluded that the sequential dynamic is a low cost, effective and very fast local minima optimization heuristic for the Graph Bisection Problem. © 2005 Elsevier B.V. All rights reserved.",
year = "2004",
title = "Large Scale Simulations of a Neural Network Model for the Graph Bisection Problem on Geometrically Connected Graphs",
volume = "18",
keywords = "Geometrically Connected Graphs , Graph Bisection Problem , Neural Networks",
pages = "151-156",
doi = "10.1016/j.endm.2004.06.024",
journal = "Electronic Notes in Discrete Mathematics",
author = "Salinas, Luís C. and Hernández, Gonzalo"
}
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