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For example, one point in the logic tree space could correspond to multiple logic trees.
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Probabilistic methods that should never be used are (1) multiple expert opinion, (2) logic trees, and (3) deaggregation.
By incorporating a swarm framework, the algorithm searches the solution space from multiple start points (different logic trees) instead of continuing to apply modifications on one logic tree.
The solution space, on the other hand, comprises all of the possible logic trees, where the logic trees could have multiple dimensions.
Epistemic uncertainty can be treated as logic trees [88].
For the same purpose, Zhu et al. [16] propose to utilize multiple logic paths.
A simulated annealing algorithm is used to predict logic trees.
For the specific logic tree space, note that we have a collapsing solution space from the set of all possible logic trees rather than a bijective solution space.
The total number of SNPs involved in all of the logic trees is defined as the logic tree model size s.
Because of the design of the logic tree (LT, the basic computational unit in logic regression), the size of the solution space of the logic trees increases factorially when the number of SNPs becomes larger.
To perform initializations, we first generate F fish (fish agents) and F initial logic trees.
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