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Subsequently, a model was trained on the whole training set, 5/6, using the optimized values for the parameters.
Using the optimized values of critical input elements of ANN, the experimental values of biosurfactant yield, emulsification index and surface tension showed close agreement with the model estimate.
Further studies on batch fermentation kinetics using the optimized values of the medium composition for K. marxianus NIRE-K1 and NIRE-K3 resulted in final ethanol concentration of 17.73 (86.27% of theoretical ethanol yield) and 19.01 g l−1 (94.12% of theoretical ethanol yield), respectively.
We found that this global/local approach resulted in sensitivity coefficients which differ significantly from the local sensitivities found using the optimized values.
Production of PHB was followed using the optimized values of various parameters obtained from different experiments as per Table 2. PHB production was carried out using production medium supplemented with different carbon sources at 1% (w/v), namely, dextrose, xylose, sucrose, rhamnose, mannitol, maltose, lactose monohydrate, mannose, galactose, starch, and raffinose pentahydrate.
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We then use the optimized values in a single recognition run-through on the evaluation set.
We repeated the recognition on the development set in order to obtain optimal parameters for the language model weight and the word insertion penalty and used the optimized values on the evaluation set.
Although we sought to use the optimized value for the width parameter, h, using the least-squares cross-validation (LSCV) method (see [18]; but see [28] for problems with this method), for one of the generated data sets and for the buffalo data, the method did not converge using either the R-Adehabitat toolbox or the Animal Movement Extension for ArcView 3.x [29].
Using the optimized parameter values along with values reported by others it was shown that the organic carbon distribution coefficient (Koc) of PEs correlates well with the octanol/water partition coefficient (Kow).
The DE algorithm aims to minimize the objective function using the optimized parameter values: V = (v_{1}, ldots,v_{D} ),quad V in R^{D}, (17 where V is a vector including the parameters of the objective function of D. The objective function is the mean squared error between the actual and estimated Fr.
We calculated the distributions of quantifiable features, namely GC content, core mfe, hairpin mfe and the ratio of core mfe to hairpin mfe, using the optimized reference values in the discovery pipeline (Table 3).
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