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To seek the optimal parameters of TFRWν-SVM, particle swarm optimization is also applied to optimize parameters of TFRWν-SVM.
The particle swarm optimization (PSO) algorithm is employed to optimize parameters of the adaptive gain nonlinear observer (AGNO).
In this paper, we employ SVM [ 14], which are suitable for solving small-sample learning and nonlinear and high dimension problems, to establish the pancreatic cancer classification, and improve fruit fly optimization algorithm (FOA) [ 15] to optimize parameters of SVM.
Moreover, parameter optimization is done sequentially so that we first optimize parameters and for individual data sources.
Furthermore, we relax the convergence condition to optimize parameters during the tree search stage; parameter optimization stops when the log-likelihood difference between two consecutive iterations is less than 0.1.
Using the positive control image set from step 33, optimize parameters in the CellProfiler pipeline by following the optimization guideline (File S1 ).
In addition, orthogonal array design (OAD) has been applied to optimize parameters of the improved method.
This algorithm uses PIPE algorithm to optimize tree structures and PSO algorithm to optimize parameters.
We can optimize parameters of the network structure such as junction types and end positions.
The traditional fuzzy neural network often uses BP algorithm to optimize parameters when conducting parameter identification.
In this model, genetic algorithm (GA) was used to select and optimize parameters.
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