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If the partitioning is not needed anymore, one can collapse a set of partitions.
To set up the TM, we generalize the partition model for a set of partitions Σ in a first step.
To do so, the potential characteristics of sub-components (solution domain of network design) are divided into a set of partitions and then HFC-APSO is utilized to explore/exploit each of those partitions.
As we described above, the modularity-based algorithms find a set of partitions that with high modularity Q by iteratively selecting and merging partition pairs that maximize Eq. (5).
The modularity Q is formally defined as follows: begin{aligned} Q = sum _{iin C}left{ frac{|E_{ii}|}{2|E|} - left( frac{sum _{jin C}|E_{ij}|}{2|E|} right) ^2 right}, end{aligned} (4 where C and |E| are a set of partitions and the total number of edges included in graph G, respectively, and (E_{ij}) is a number of edges between partition i and j.
By using the ARI, given a set of partitions P, |P| = m, we can compute the likelihood of a partition with respect to the others pi ϵ P as L(P| pi) = Pr(pi|P) = ∏j≠iaji, where aji is the ARI between partition pj and pi, and then select the best partition pb with the maximum likelihood.
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We introduce a set of partition Δ n ={x0,⋯1,x,x n } of [a,b], where x i (i=0(1)n) are called nodes of the partition.
Calculating a new putative near-solidus melt composition using a set of partition coefficients for each element in each mineral, the modal mineral assemblage of the peridotite, and the composition of the starting peridotite.
This process continues until a set of partitioning criteria are no longer met, resulting in terminal nodes.
We propose here, differently from most of consensus clustering algorithms, a methodology that selects one particular partition in a set of obtained partitions.
A second, vaguely architectonic piece nearby looks like a set of flexible partitions; its hinged form is based on a common accordion-style Mexican child's toy.
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CEO of Professional Science Editing for Scientists @ prosciediting.com