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Conflict free paths of the mobile vessels are generated automatically by an approach from graph theory and subsequent heuristic conflict resolution.
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This approach is derived from graph theory and aims to describe complex population structures based on the distribution of the genetic covariance among the studied populations using SSR molecular data.
The orthogonal crystallographic representations of the icosahedral group are classified, and their intersections are studied in some detail, using a combinatorial approach which involves results from graph theory and their spectra.
Even if many methods have been used to solve such problems, a new approach based on results borrowed from graph theory has been introduced in recent works.
Conventional approaches focus on mining discriminative subgraphs from graph view alone.
The evidence for the failure of the mapping approach in interspecific comparisons comes from the de novo approach of graph based clustering using RepeatExplorer.
In our approach, a graph grammar is derived automatically from a state machine to summarize the hierarchy of states.
Further, it allows for the use of methods from graph theory and complex network analysis, which strengthen our approach.
a Read from graph.
Values were estimated from graph.
Another approach is graph indexing, which is frequently used as an optimization technique in graph-mining.
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