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In the case of optimization of the fuzzy system for response integration, the genetic algorithm not only adjusts the number of membership functions and rules, but also allows the variation on the type of logic (type-1 or type-2) and the change in the inference model (switching to Mamdani model or Sugeno model).
This observation is complementary to current knowledge of pilocytic astrocytoma's biology and indicates that for targeted therapy three molecular subgroups of the tumor must be considered, particularly in the case of optimization of the treatment of optic nerve PAs.
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Even in the case of Chebyshev optimization, auditory warping appears to improve the numerical conditioning of the filter design problem; this applies also to optimization under the Hankel norm which includes an optimal Chebyshev design internally as an intermediate step.
One of the main advantages of simulation-based optimization is that it not necessary to provide analytical expression of objective and constraints function as in the case of mathematical optimization.
Hence, the present approach is especially useful for parametric studies, such as in the case of design optimization and exploration of flow phenomena.
Finally, like in the case of the optimization over, we can transform (40) into the following convex problem: (41).
In the case of continuous optimization, this can be achieved in a straightforward manner by linearly mapping each random-key from the genotype space to the design space of the optimization task.
In [8], an iterative algorithm similar to the LMS (least mean squares) algorithm was suggested to update the m j and r in the case of MSE optimization: m ( n e x t, j ) = m ( j ) + 2 α ( d i - y i ) ∂ y i ∂ m ( j ) ∀ j ∈ A (6) r ( n e x t ) = r + 2 β ( d i - y i ) ∂ y i ∂ r (7).
Generally, in the case of such optimization approaches, and not limited to shake flasks studies, the quantitative analysis of mRNAs, especially for C-P4H and collagen in our case, seems to be a good indicator for the quality of the cultivation.
Parsimony analyses were performed in WinClada [ 61] using ACCTRAN and DELTRAN tracing options to examine alternative scenarios in the case of ambiguous optimizations.
The structural optimization is realized via GAs whereas in the case of the parametric optimization we proceed with a standard least square method based learning.
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