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Exact(9)
(3) Use the genetic algorithm to optimize the neural network response surface as the objective function.
Secondly, two-degree-of-freedom (2-DOF) PID control is applied to the winding process, with the controller having been designed to use the Genetic Algorithm (GA).
The approach is to use the genetic algorithm for determining the optimized complex slip surface (CSS) pattern as well as an optimized slope incline ratio simultaneously.
Based on available literature and our experimental data, we develop a mathematical model of virus- and dsRNA-triggered signaling pathways leading to type I IFN gene expression during the primary response, and use the genetic algorithm to optimize all rate constants in the model.
In this paper, we use the genetic algorithm (GA).
They use the genetic algorithm for making a guess of initial parameter estimates.
Similar(51)
The microstructure optimization code is developed using the micro-genetic algorithm and the finite element method.
In terms of prediction accuracy for testing datasets, GA has a better performance compared to the differential evolution (DE) approach, which motivates the choice to use the genetic algorithm-extreme learning model (GA-ELM).
Therefore, we use the genetic algorithms (GA) to perform optimizations [47, 48].
The optimization methodology, using the genetic algorithm and the formulation of the problem are detailed.
This paper presents the optimal design of the magnetic microactuator using the genetic algorithm.
More suggestions(15)
use the genetic knowledge
use the genetic information
use the genetic workhorse
use the genetic association
use the flawed algorithm
use the ensemble algorithm
use the original algorithm
use the genetic risk
use the combined algorithm
use the same algorithm
use the genetic father
use the genetic model
use the genetic supermarket
use the genetic programming
use the genetic transcription
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