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A save-then-transmit protocol was proposed in [7,8] to optimize the system performance by finding the optimal save-ratio.
We use physical programming as an effective approach to optimize the system structure within this multi-objective optimization framework.
The paper proposes resource allocation algorithms that aim to optimize the system performance over the sum of the optimal user utility functions by employing the effective capacity theory.
The anticipated improvement rate is also determined by finding the levels of the factors in order to optimize the system which uses Taguchi's single response optimization methodology.
In this paper, we have used a simple brute-force search technique to optimize the system parameters, while it is also possible to use non-linear optimization techniques.
A velocity threshold is used to optimize the system performance.
Genetic algorithm is employed to optimize the system performance.
That means that there is a need for co-ordination to optimize the system.
This knowledge can be used to optimize the system in terms of power consumption and stability.
The ratings of the HESC system are investigated in order to optimize the system energy efficiency.
We tried hard to optimize the system to generate "better" piPSCs for application.
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