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Statements

Subject Item
dbr:LASCNN_algorithm
rdfs:label
LASCNN algorithm
rdfs:comment
In graph theory, LASCNN is a Localized Algorithm for Segregation of Critical/Non-critical Nodes The algorithm works on the principle of distinguishing between critical and non-critical nodes for network connectivity based on limited topology information. The algorithm finds the critical nodes with partial information within a few hops. This algorithm can distinguish the critical nodes of the network with high precision, indeed, accuracy can reach 100% when identifying non-critical nodes. The performance of LASCNN is scalable and quite competitive compared to other schemes.
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dbc:Networks dbc:Network_theory dbc:Graph_algorithms
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64946153
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1074095315
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dbr:Critical_point_(network_science) dbr:Strength_of_a_graph n8:Critical_Nodes_Application.png dbr:Cheeger_constant_(graph_theory) dbc:Networks dbc:Graph_algorithms dbr:Connectivity_(graph_theory) dbr:Dynamic_connectivity dbr:Depth-first_search dbr:Breadth-first_search dbc:Network_theory dbr:PWCT
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In graph theory, LASCNN is a Localized Algorithm for Segregation of Critical/Non-critical Nodes The algorithm works on the principle of distinguishing between critical and non-critical nodes for network connectivity based on limited topology information. The algorithm finds the critical nodes with partial information within a few hops. This algorithm can distinguish the critical nodes of the network with high precision, indeed, accuracy can reach 100% when identifying non-critical nodes. The performance of LASCNN is scalable and quite competitive compared to other schemes.
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dbr:Mahmoud_Samir_Fayed
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dbr:LASCNN_algorithm
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wikipedia-en:LASCNN_algorithm
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dbr:LASCNN_algorithm