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We explore the geometry of networks in terms of an n-dimensional Euclidean embedding represented by the Moore-Penrose pseudo-inverse of the graph Laplacian (L+). The reciprocal of squared distance from each node i to the origin in this n-dimensional space yields a structural centrality index (C*(i)) for the node, while the harmonic sum of individual node structural centrality indices, Pi 1/C * (i),...
Existing network damage assessment method fall short because they either lack correlation adjustment among indexes or without conclusive evidence to demonstrated the degree does represent the real situation of the network. This paper proposed a method to adjustment index correlation based on Orthogonalization. The advantages of this method for evaluation damage degree of network have been demonstrated...
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