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The results show that: The Model A of carrier electronic warfare airplane is better than Model B on stealth performance and on discover probability by radar detection effectively.
However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks.
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Optimal solutions were obtained for the following CS parameters: Levy distribution parameter = 1.5 and Alien eggs discovering probability (pa) = 0.25.
And, it is an innovative way to find the frequent probability patterns, which may be efficiently used for discovering probability motifs in the further studies.
We analysed ∼3 × 10 genes in such a way, and detected from 0 to 8 cases of region T extension due to accidental factors with a discovering probability of the given interval equal to 95%.
Thus, the main steps of the algorithm to discover the probability subgraph isomorphism are as follows: Firstly, according to the probability graph g and g′, get the associated circuit N and N′, then calculate the node voltages sequence matrix S and S′; Next, using the Hungarian algorithm to get the assignment matrix M and the mismatch values VMval.
Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters.
Then based on the probability graph isomorphism algorithm, the hierarchical clustering method is adopted to cluster subgraphs to discover frequent probability patterns from the clusters.
In this setting, the purpose of a learning algorithm is to discover the probability distribution p that captures the "functional" relationships that may exist between X and Y.
forward degree of a node at hops Generic routing overhead (packets) Routing overhead of protocol Route optimality Length of an optimal path Total number of node-disjoint paths Normalized weight of paths of length Optimal path discovery probability No. of hops paths discovered successfully Probability of path discovery Exp.
The next sections will introduce the method of probability graph isomorphism evaluation and the algorithm of two-step hierarchical clustering for discovering frequent probability subgraph.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com