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Attributes and levels were combined using an orthogonal design to produce a number of discrete hypothetical treatments.
The seven attributes and three levels were combined using a published orthogonal array (available at: http://neilsloane.com/oadir/).com/oadir/
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Data synthesis Study level outcomes from randomised trials were combined using random effects network meta-analyses.
Single session data were analyzed at the first level, and the 2 runs from each subject were combined using a fixed-effects analysis at the second level.
Epidemiological and food survey data were combined, using a predictive modelling approach, to estimate a dose-response relationship for L. monocytogenes levels and incidence of listeriosis.
The runs were combined using LogCombiner [ 112].
These two groups were combined using 'AND'AND
Finally, independent runs were combined using LogCombiner.
GEFTS uses a dynamic nonlinear weighting system wherein the outputs from several base-level GRNNs are combined using a combiner GRNN to produce the final output.
These components are combined using multiobjective optimization.
These parameters are combined using Genetic Programming.
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