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SSSP (single-source shortest path): computing the shortest paths to all vertexes from a given vertex.
In both problems the cost is associated with a set of paths from a given vertex r to all the leaves of the constructed tree.
It can be regarded as a measure of how much time it takes to spread information into the network from a given vertex.
Another approach to characterize the connectivity of a gene cluster is based on the so-called the shortest path function (SPF): where the shortest path along the network from a given vertex node i to some another vertex node j is denoted by d i, j.
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Similarly, probability of finding a particle at a given vertex is increased as the fugacity increases.
Algorithm 2 (Fig. 3 ▶): Computation of the vertex star of a given vertex i in the -graphs.
The closer the shell morphology is to a given vertex of the pyramid, the more important the corresponding task.
The algorithms for the traversals given below start from any given vertex v in the network.
It repeatedly finds shortest paths from a given start vertex to a given goal vertex while the edge costs of a graph change or vertices are added or deleted.
The shortest path problem for weighted graphs consists of finding a path going from a given source vertex to a given target vertex while minimizing a cost function given by the sum of the costs of the arcs involved in the path.
For the local graph clustering problems, the LRW procedure can efficiently find the cluster from a given seed vertex.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com