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Experiments are designed based on Taguchi's Design of Experiment, for seven input parameters varied through three levels, an L18 Orthogonal array is chosen.
To perform the required NNM training, output responses predicted from the cell model are first generated by using all possible combinations of eleven key input parameters varied over practical ranges of interest.
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A promising alternative is in the use of design of experiments, a statistical method that allows defining a structured and restricted number of simulations for which all input parameters vary simultaneously.
The model was verified using a nearly orthogonal experiment design where the input parameters were varied randomly to generate combinations not previously considered.
To simulate the operating behavior of such a device, an emulator (input parameters were varied for a given target) can be designed and implemented based on a NLARX (nonlinear autoregressive with exogenous inputs) model.
For RoMANS, a new ensemble technique was employed in which input parameters were varied to explore the range, variability, and model sensitivity of source attribution results and statistical measures of model fit over thousands of trials for each set of concentration measurements.
In the absence of reliable data, the values of input parameters are varied between upper and lower bounds with the PDF defined by an appropriate distribution function.
Additionally, probabilistic sensitivity analysis was performed using Monte Carlo simulation to evaluate the multivariate uncertainty in the model, i.e., input parameters were varied simultaneously over specified ranges.
The input parameters were varied simultaneously over specified ranges.
All input parameters were varied by drawing from their probability distribution.
Figure 2 shows the mean, median, and distribution of total costs when the range of input parameters is varied.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com