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The statistical tools like design of experiments (DoE) permit the investigation of the process via simultaneous changing of factors' levels using reduced number of experimental runs.
Since all possible combinations of factors' levels, are not considered in the Taguchi method, the response values of the possible unpracticed treatments are estimated using the artificial neural network (ANN).
The application of DoE for the improvement of the MALDI measurement of PLA stated that the best combination of factors (levels) was the following: matrix (s-DHB), proportion analyte/matrix (1/5 V/V), and no use of cationization agent.
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Table 2 Algorithms' parameters along with their levels No. of factors Level Low Medium High Parameters 1 2 3 1 MaxIt 100 150 200 2 N pop 30 50 70 3 P c 0.7 0.8 0.9 4 P m 0.2 0.25 0.2.
Each experiment defines one specific combination of factor levels.
In full factorial designs, the experimental runs are performed at all combinations of factor levels.
The simplest are factorial experiments, where all factors are varied simultaneously at a limited number of factor levels [26].
We consider two replicates for each combination of factor levels; hence, for this instance, 24 treatment combinations are arranged.
This property is satisfied if, for example, for each pair of factors, every combination of factor levels exists and occurs equally often.
The selected model predicts a priori mean and standard deviation of picking times for any given combination of factor levels.
A factorial experiment is defined as one in which responses are observed for every combination of factor levels.
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