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Genetic algorithms are one of the most adaptable optimization algorithms.
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Environment-Adaptable Fast optimization.
In order to efficiently find an optimal configuration, Environment-Adaptable Fast (EAF) optimization utilizes calculated signal-to-interference-and-noise ratio (SINR) and narrows down the searching space (Jun et al., Environment-adaptable efficient optimization for programming of reconfigurable Radio Frequency (RF) receivers, 2014).
Interlimb coordination is adapted, as an optimization mechanism to obtain as much speed as possible in face of constraints imposed [ 54], showing that an effective front crawl swimming technique must be sufficiently flexible and adaptable [ 55].
Besides an optimal network planning including adaptable transmit powers, also a symbiotic optimization over different networks and network layers is implemented, a new concept in network cooperation.
By using fully parameterized models, the optimization approach is adaptable to other scaffold designs and bone defect situations.
Thus, a fast optimization algorithm called Environment-Adaptable Fast (EAF) optimization was proposed for speeding up the optimization of a reconfigurable RF front-end in a dynamic spectrum environment [9].
Asset management and optimization is becoming increasingly adaptable for distribution utilities with the help of developments in the digital and wireless technology.
However in order to make the model more flexible and adaptable to human decision process, the optimization model can be expressed as fuzzy nonlinear programming problems with fuzzy numbers.
Using the estimated results, the SINR formula was calculated and used for the Environment-Adaptable Fast Multi-Resolution (EAF-MR) optimization, which was designed by applying the EAF optimization to multi-resolution optimization.
The model is recommended for further process developments and reactor optimization, its parameters being easily adaptable for every type of P2Ox.
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