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Architectural parameters were reduced by about 20% in ovx rats.
The microvascular perfusion parameters were reduced compared to the normal value of healthy subjects (MFI = 3).
The parameters were reduced as much as possible, to only two.
Correlations between (E 0, δrj) and fitting parameters were reduced by weighting the XAFS data by k n (n = 1, 2, 3).
However, in the prioritization of sub-watersheds made by Gajbhiye et al. (2013b), 14 geomorphic parameters were taken, whereas in the PCA-based scheme, parameters were reduced from 14 to 3, which saves time.
We found, however, that magnetic concentration parameters were reduced markedly during refrigerated storage of samples for 3 years after collection, particularly in samples from the deeper part of the lake.
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Therefore, the amount of information about the parameters is reduced.
The degree of coupling between the parameters is reduced.
Therefore, the fitting procedure was modified and the number of free parameters was reduced.
Computational modeling involves parameterization, where the number of calibration parameters are reduced (Refsgaard, 1997).
Consequently, controller design and tuning become transparent as the number of required model parameters is reduced.
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