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The definitive quality of the found solutions generated by the optimization methods, can only be evaluated if the 'correct' solution is known.
However, note that these qualitative aspects have not been included in the objective function (SSE) used by the optimization methods: thus, we cannot objectively and fairly compare the methods along this dimension.
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Numerical optimization results show that the volute vibration is reduced by the optimization method.
In this example, data set 3 will be fit, and all the parameter values and the fit statistic used by the optimization method will be stored in the file "fit_info.out".
The volume fractions of the primary C S H predicted by the optimization method were found to be in close agreement with the experimentally obtained values from EDS.
By comparison, noise levels obtained by the optimization method are lower than those obtained by INM.
The adaptive bandwidth for the BLF has already been considered in [9], where the σ r is adjusted along with an offset parameter by the optimization method with some training images.
The optimum conditions were determined by the optimization method to yield a heightened performance.
In this section, analytical results on accessibility as measured by the optimization method and catchment models are provided.
From the remaining individuals, n Train =25,50 and 80 were selected in the training population by random sampling or by the optimization method described in the Methods section.
Subsequently, to minimize the bias introduced by the optimization method, we performed a neutral evolution, introducing L mutations that did not change the MFE structure.
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