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This paper addresses several types of potential conflicts and consistency properties with a systematic and rigorous approach: graph theory, network flow technology and colored Petri nets are applied for specifying and verifying a secure interoperation design.
This concept consists of three different parts: (i) a probabilistic fragility analysis for each individual physical element (i.e. a building or an infrastructure element), (ii) a composite index methodology for the measurement of community disaster resilience, and (iii) a complex network approach (graph theory) for the assessment of the resilience of urban systems as a whole.
Following this approach, graph metrics and the GMV of nodes were all normalised (z-scored) on a within-subject level.
In our approach, graph transition energy is defined to quantify the similarity between collections of images.
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Research in assembly planning can be categorised into three types of approach: graph-based, knowledge-based and artificial intelligence approaches.
To address the limitations of the existing methods, we propose a novel approach, Graph-regularized Dual Lasso (GDL), which simultaneously learns the association between SNPs and genes and refines the prior networks.
Available data from all surveys were analyzed using a thematic content analysis approach; graphs were used to provide visual representations of the information.
Normally, various social computing related techniques include statistical approaches, graph based approaches and so forth.
Graph Based Approaches: Graph theory related techniques like minimal spanning tree and max-flow min-cut etc. are used for clustering.
The metabolic pathfinding problem itself can be further divided into two different approaches: graph-based pathfinding and constraint-based pathfinding.
Experimental results show that the proposed algorithms (GM-SMCC and EGM-SMCC) can lead to performance superior to other compared feature-based approaches, graph-based approaches, and collective classification algorithms.
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