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Simulation results show the effectiveness of the chosen controller design and parameter setup.
The parameter setup and tables with the predictive accuracy of models used in the case studies.
For each parameter setup, we generated 10 random data sets for training and testing.
Second, the optimal parameter setup is derived from the optimal rate vector.
The proposed technique is also applicable to numerous other representations, without any change in the parameter setup.
The cumulative distribution function (CDF) of the received constellation EVM obtained with this parameter setup is shown in Fig. 16.
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The parameter setups of the DM, MDI, and NMF methods use the same values as the best performing systems in the experiments of our previous studies [17, 18].
For this real-world event, model scenarios with only water and with inclusion of sediment with different parameter setups were performed.
The parameter setups were as follows: JTT substitution model, four chains, one million generations, two runs, sampling every 100 generations and discarding a burn-in of 250,000 generations.
The parameter setups were as follows: model, Jones-Taylor-Thornton (JTT) [ 54]; bootstrap, 1000 replicates; and gap/missing data, pairwise-deletion.
This inevitably results in potentially new parameter setups for which we have to update our understanding of their synergistic effects on antaRNA.
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