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Optimized ANFIS models were compared to statistical regression models and demonstrated improved predictions in all comparisons.
Compared to the type III model, the type I model demonstrated improved predictions in all cases.
Only the Extended CSTR and Pseg methods produced realistic and conservative predictions in all cases.
Reasonably good agreement exists between LIF [NO] measurements and predictions in all flames.
However, the finite Reynolds number kernel gives better predictions in all cases than those made using the Basset history force.
Furthermore, it has been found that the technique is quite general and yields excellent predictions in all cases.
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A predictive model using RRV during the last SBT provided optimal accuracy of prediction in all patients, with improved accuracy when combined with clinical impression or RSBI.
Furthermore, prediction in all of the remainder irrigation statuses also improves.
The central composite design (CCD) was used as an experimental design to obtain equal prediction in all directions from the center in which the variables vary in 5 levels with 5 axial points and 5 replicates at the center.
In one of the 20 pairs (pair_ID = 7), there was a different prediction in all FFPE replicates (low GGI risk) compared to all the FF replicates (high GGI risk).
De-regressed proofs (DRP) were used as response variables for genomic prediction in all approaches.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com