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Self-Organizing maps can discover topological and multidimensional patterns using a variety of methods. We apply a parallel algorithm proposed by the authors (ParaSOM), which yields closer and denser approximations than other methods in a fraction of iterations, to a twodimensional pattern in a parallel environment to demonstrate a high degree of neuron independence. In a second implementation, pieces of a two-dimensional input space are distributed over a network and processed by independent ParaSOM algorithms.

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This paper examines the application of graph theory (GTH) in facilities design and questions whether existing methodologies can be improved. The paper proposes a new approach which introduces the concept of a maximally weighted planar graph (MWPG), in contrast to the more usual maximally planar weighted graph (MPWG).

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