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Several process optima were identified by the genetic algorithm.
Then, the optimal thresholds are obtained by the genetic algorithm.
The locations of the piezoelectric sensors are optimized by the Genetic Algorithm based on maximizing the observability gramian matrix.
The optimal area and position of piezoelectric patches are also obtained by the genetic algorithm.
Design examples generated by the genetic algorithm are given to demonstrate the feasibility of the method.
In the next step, a fitness function is optimized by the genetic algorithm (GA) program.
The PID gain parameters are optimized by the genetic algorithm (GA).
This latter is designed by the genetic algorithm as criteria for noise reduction.
The neural network is trained by the genetic algorithm (GA) to avoid the 'local minimum' phenomenon in most NN applications.
Based on the proposed formation configuration strategy, the trajectories of followers are solved by the genetic algorithm.
The results generated by the genetic algorithm define a new combination of shape features for alternative designs.
More suggestions(18)
by the genetic framework
by the present algorithm
by the genetic analysis
by the current algorithm
by the genetic risk
by the genetic makeup
by the genetic counselor
by the evolutionary algorithm
by the above algorithm
by the genetic code
by the genetic background
by the genetic association
by the genetic mutation
by the genetic architecture
by the genetic diversity
by the heuristic algorithm
by the genetic distance
by the hybrid algorithm
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