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First, we transform Eq. (10) to a convex problem by changing the optimized variable and ignoring some constraints and solve it by the Lagrange dual method.
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Furthermore, sensitivity analysis reveals that some formation energies can vary substantially without changing the optimized objective value significantly.
Polarization was changed by changing the orientation of the laser.
Moreover, its field emission property was also optimized by changing the nanorods density and dimension.
The field emission property was also optimized by changing the nanorods density and dimension.
Furthermore, the local TBR was optimized by changing the material proportion for each Pn level (1 5 MW/m2).
The crystallization condition was subsequently optimized by changing the concentrations of precipitant, salts, and buffer around the initial hit condition.
Different transfer functions e.g. TANSIG, LOGSIG and PURELIN were used and the performance of the ANN was optimized by changing the number of neurons in the hidden layers.
However, these properties could be optimized by changing the crosslinking density (either azobenzene or side-chain LC concentration) in the polymeric network.
The power distribution in the core was optimized by changing the uranium enrichment to maintain the fuel temperature at less than the limit (1600 °C).
The structure of the as-prepared nanocomposites was further optimized by changing the amount of GO to exploit better super-capacitance properties.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com