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The training algorithm for this network is trainbr.
Particle swarm optimization (PSO) is proposed as the training algorithm for GN and RGN.
Another design decision is the training algorithm for the constituent weak learners.
Framework of the training algorithm for the proposed FRBF Network is demonstrated in Fig. 1.
The training algorithm for the NNFLE transformation proposed in this study is described in Fig. 11.
The training algorithm for the NFLE transformation proposed in our previous work [13] is described in Fig. 4.
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The training algorithms for all the parameters in the composite model are developed using the expectation-maximization framework.
Third, both the basic ELM and the OP-ELM are used as the training algorithms for each ensemble in the new structure.
The pseudocode of this training algorithm for the discriminative score weights is given in Algorithm 1.
The use of the BFGS training algorithm for ANN, and the RBF kernel function for SVR models are recommended as useful options for simulating hydrological phenomena.
Section "Convolutional neural networks" explains the architecture of CNN followed by the proposed training algorithm for the CNN architecture.
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