Examples of using Directed graph in English and their translations into Hungarian
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On cycles of directed graphs.
Directed graphs are the problem.
Algorithm for directed graphs.
Directed graphs with nonnegative weights.
These are called directed graphs.
Directed graph labeled with pairwise preferences d[*,*].
Transitive closure of directed graphs(Warshall's algorithm).
Sysło(1982) generalized these methods to directed graphs.
Shortest paths in directed graphs(Floyd's algorithm).
Directed graphs with arbitrary weights without negative cycles.
Reduce the program to a directed graph and analyze the graph.
Johnson's algorithm is a way to find theshortest paths between all pairs of vertices in an edge-weighted, directed graph.
Given a directed graph G with n vertices, having start vertex u and end vertex v.
Maltego- An interactive data mining tool that renders directed graphs for link analysis.
A directed graph is strongly connected if there is a path from u to v and from v to u for any u and v in the graph. .
A transitive orientation is an orientation such that the resulting directed graph is its own transitive closure.
A directed graph is said to be aperiodic if there is no integer k> 1 that divides the length of every cycle of the graph. .
Apache2GDL is a Perl script that parses an Apache log file andgenerates a directed graph of visitors' movement in GDL format for visualization with aiSee.
Given a directed graph(V, A) with source node s, target node t, and cost wij for each edge(i, j) in A, consider the program with variables xij.
A simple directed acyclic graph In computer science and mathematics, a directed acyclic graph, also called a dag or DAG, is a directed graph with no directed cycles;
The first part is creating a general directed graph which is representing the relationships of the tables and necessary metadata are stored in this model, like foreign keys, primary keys.
This matches the lower bound of n- 1.[3] An analogous competitive lower bound of Ω(n) also holds for randomized algorithms that know the coordinates of each node in a geometric embedding. If instead of visiting all nodes just a single"treasure" node has to be found, the competitive bounds are Θ(n2)on unit weight directed graphs, for both deterministic and randomized algorithms.
It is defined here for undirected graphs; for directed graphs the definition of path requires that consecutive vertices be connected by an appropriate directed edge.
The single-destination shortest path problem,in which we have to find shortest paths from all vertices in the directed graph to a single destination vertex v. This can be reduced to the single-source shortest path problem by reversing the arcs in the directed graph.
Given a directed graph G=( V, E){\displaystyle G=(V, E)} and two vertices s{\displaystyle s} and t{\displaystyle t}, we are to find the maximum number of paths from s{\displaystyle s} to t{\displaystyle t}.
The all-pairs shortest paths problem for unweighted directed graphs was introduced by Shimbel(1953), who observed that it could be solved by a linear number of matrix multiplications that takes a total time of O(V4).
A regular directed graph must also satisfy the stronger condition that the indegree and outdegree of each vertex are equal to each other.[1] A regular graph with vertices of degree k is called a k‑regular graph or regular graph of degree k.
We now define a new weighted directed graph D′=⟨ V′, E′⟩{\displaystyle D^{\prime}=\langle V^{\prime}, E^{\prime}\rangle} in which the cycle C{\displaystyle C} is"contracted" into one node as follows.
For example, when searching the directed graph below beginning at node A, the sequence of traversals is either A B D B A C A or A C D C A B A(choosing to first visit B or C from A is up to the algorithm).
The algorithm takes as input a directed graph D=⟨ V, E⟩{\ displaystyle D=\ langle V, E\ rangle} where V{\ displaystyle V} is the set of nodes and E{\ displaystyle E} is the set of directed edges, a distinguished vertex r∈ V{\ displaystyle r\ in V} called the root, and a real-valued weight w( e){\ displaystyle w( e)} for each edge e∈ E{\ displaystyle e\ in E}.